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Initial commit: Hermes Agent skills collection

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- Trading skills (OKX, dividend, lottery, quantitative)
- Creative skills (ASCII art, diagrams, video)
- Development skills (GitHub, debugging, TDD)
- Research skills (arXiv, blog monitoring)
- Productivity skills (email, documents, notes)
- MCP integration skills
- Custom user skills
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Hermes Skills Manager
2026-07-05 02:31:15 -04:00
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openclaw-imports/clawhub-skills-polyfill/CHANGELOG.md
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# Changelog
## v2.1.0 (2026-04-11)
- Version bump to 2.1.0
## v2.0.1 (2026-02-06)
- Simplified documentation
- Removed gov-related content
- Optimized for ClawHub publishing
## v2.0.0 (2026-02-06)
- Added 9 international search engines
- Enhanced advanced search capabilities
- Added DuckDuckGo Bangs support
- Added WolframAlpha knowledge queries
## v1.0.0 (2026-02-04)
- Initial release with 8 domestic search engines
openclaw-imports/clawhub-skills-polyfill/CHANNELLOG.md
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# Multi Search Engine
## 基本信息
- **名称**: multi-search-engine
- **版本**: v2.0.1
- **描述**: 集成16个搜索引擎（7国内+9国际），支持高级搜索语法
- **发布时间**: 2026-02-06
## 搜索引擎
**国内（7个）**: 百度、必应CN、必应INT、360、搜狗、微信、神马
**国际（9个）**: Google、Google HK、DuckDuckGo、Yahoo、Startpage、Brave、Ecosia、Qwant、WolframAlpha
## 核心功能
- 高级搜索操作符（site:, filetype:, intitle:等）
- DuckDuckGo Bangs快捷命令
- 时间筛选（小时/天/周/月/年）
- 隐私保护搜索
- WolframAlpha知识计算
## 更新记录
### v2.0.1 (2026-02-06)
- 精简文档，优化发布
### v2.0.0 (2026-02-06)
- 新增9个国际搜索引擎
- 强化深度搜索能力
### v1.0.0 (2026-02-04)
- 初始版本：8个国内搜索引擎
## 使用示例
```javascript
// Google搜索
web_fetch({"url": "https://www.google.com/search?q=python"})
// 隐私搜索
web_fetch({"url": "https://duckduckgo.com/html/?q=privacy"})
// 站内搜索
web_fetch({"url": "https://www.google.com/search?q=site:github.com+python"})
```
MIT License
openclaw-imports/clawhub-skills-polyfill/HEARTBEAT.md
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## Self-Improving Check
- Read `./skills/self-improving/heartbeat-rules.md`
- Use `~/self-improving/heartbeat-state.md` for last-run markers and action notes
- If no file inside `~/self-improving/` changed since the last reviewed change, return `HEARTBEAT_OK`
openclaw-imports/clawhub-skills-polyfill/SKILL.md
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---
name: Self-Improving + Proactive Agent
slug: self-improving
version: 1.2.16
homepage: https://clawic.com/skills/self-improving
description: "Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when (1) a command, tool, API, or operation fails; (2) the user corrects you or rejects your work; (3) you realize your knowledge is outdated or incorrect; (4) you discover a better approach; (5) the user explicitly installs or references the skill for the current task."
changelog: "Clarifies the setup flow for proactive follow-through and safer installation behavior."
metadata: {"clawdbot":{"emoji":"🧠","requires":{"bins":[]},"os":["linux","darwin","win32"],"configPaths":["~/self-improving/"],"configPaths.optional":["./AGENTS.md","./SOUL.md","./HEARTBEAT.md"]}}
---
## When to Use
User corrects you or points out mistakes. You complete significant work and want to evaluate the outcome. You notice something in your own output that could be better. Knowledge should compound over time without manual maintenance.
## Architecture
Memory lives in `~/self-improving/` with tiered structure. If `~/self-improving/` does not exist, run `setup.md`.
Workspace setup should add the standard self-improving steering to the workspace AGENTS, SOUL, and `HEARTBEAT.md` files, with recurring maintenance routed through `heartbeat-rules.md`.
```
~/self-improving/
├── memory.md # HOT: ≤100 lines, always loaded
├── index.md # Topic index with line counts
├── heartbeat-state.md # Heartbeat state: last run, reviewed change, action notes
├── projects/ # Per-project learnings
├── domains/ # Domain-specific (code, writing, comms)
├── archive/ # COLD: decayed patterns
└── corrections.md # Last 50 corrections log
```
## Quick Reference
| Topic | File |
|-------|------|
| Setup guide | `setup.md` |
| Heartbeat state template | `heartbeat-state.md` |
| Memory template | `memory-template.md` |
| Workspace heartbeat snippet | `HEARTBEAT.md` |
| Heartbeat rules | `heartbeat-rules.md` |
| Learning mechanics | `learning.md` |
| Security boundaries | `boundaries.md` |
| Scaling rules | `scaling.md` |
| Memory operations | `operations.md` |
| Self-reflection log | `reflections.md` |
| OpenClaw HEARTBEAT seed | `openclaw-heartbeat.md` |
## Requirements
- No credentials required
- No extra binaries required
- Optional installation of the `Proactivity` skill may require network access
## Learning Signals
Log automatically when you notice these patterns:
**Corrections** → add to `corrections.md`, evaluate for `memory.md`:
- "No, that's not right..."
- "Actually, it should be..."
- "You're wrong about..."
- "I prefer X, not Y"
- "Remember that I always..."
- "I told you before..."
- "Stop doing X"
- "Why do you keep..."
**Preference signals** → add to `memory.md` if explicit:
- "I like when you..."
- "Always do X for me"
- "Never do Y"
- "My style is..."
- "For [project], use..."
**Pattern candidates** → track, promote after 3x:
- Same instruction repeated 3+ times
- Workflow that works well repeatedly
- User praises specific approach
**Ignore** (don't log):
- One-time instructions ("do X now")
- Context-specific ("in this file...")
- Hypotheticals ("what if...")
## Self-Reflection
After completing significant work, pause and evaluate:
1. **Did it meet expectations?** — Compare outcome vs intent
2. **What could be better?** — Identify improvements for next time
3. **Is this a pattern?** — If yes, log to `corrections.md`
**When to self-reflect:**
- After completing a multi-step task
- After receiving feedback (positive or negative)
- After fixing a bug or mistake
- When you notice your output could be better
**Log format:**
```
CONTEXT: [type of task]
REFLECTION: [what I noticed]
LESSON: [what to do differently]
```
**Example:**
```
CONTEXT: Building Flutter UI
REFLECTION: Spacing looked off, had to redo
LESSON: Check visual spacing before showing user
```
Self-reflection entries follow the same promotion rules: 3x applied successfully → promote to HOT.
## Quick Queries
| User says | Action |
|-----------|--------|
| "What do you know about X?" | Search all tiers for X |
| "What have you learned?" | Show last 10 from `corrections.md` |
| "Show my patterns" | List `memory.md` (HOT) |
| "Show [project] patterns" | Load `projects/{name}.md` |
| "What's in warm storage?" | List files in `projects/` + `domains/` |
| "Memory stats" | Show counts per tier |
| "Forget X" | Remove from all tiers (confirm first) |
| "Export memory" | ZIP all files |
## Memory Stats
On "memory stats" request, report:
```
📊 Self-Improving Memory
HOT (always loaded):
memory.md: X entries
WARM (load on demand):
projects/: X files
domains/: X files
COLD (archived):
archive/: X files
Recent activity (7 days):
Corrections logged: X
Promotions to HOT: X
Demotions to WARM: X
```
## Common Traps
| Trap | Why It Fails | Better Move |
|------|--------------|-------------|
| Learning from silence | Creates false rules | Wait for explicit correction or repeated evidence |
| Promoting too fast | Pollutes HOT memory | Keep new lessons tentative until repeated |
| Reading every namespace | Wastes context | Load only HOT plus the smallest matching files |
| Compaction by deletion | Loses trust and history | Merge, summarize, or demote instead |
## Core Rules
### 1. Learn from Corrections and Self-Reflection
- Log when user explicitly corrects you
- Log when you identify improvements in your own work
- Never infer from silence alone
- After 3 identical lessons → ask to confirm as rule
### 2. Tiered Storage
| Tier | Location | Size Limit | Behavior |
|------|----------|------------|----------|
| HOT | memory.md | ≤100 lines | Always loaded |
| WARM | projects/, domains/ | ≤200 lines each | Load on context match |
| COLD | archive/ | Unlimited | Load on explicit query |
### 3. Automatic Promotion/Demotion
- Pattern used 3x in 7 days → promote to HOT
- Pattern unused 30 days → demote to WARM
- Pattern unused 90 days → archive to COLD
- Never delete without asking
### 4. Namespace Isolation
- Project patterns stay in `projects/{name}.md`
- Global preferences in HOT tier (memory.md)
- Domain patterns (code, writing) in `domains/`
- Cross-namespace inheritance: global → domain → project
### 5. Conflict Resolution
When patterns contradict:
1. Most specific wins (project > domain > global)
2. Most recent wins (same level)
3. If ambiguous → ask user
### 6. Compaction
When file exceeds limit:
1. Merge similar corrections into single rule
2. Archive unused patterns
3. Summarize verbose entries
4. Never lose confirmed preferences
### 7. Transparency
- Every action from memory → cite source: "Using X (from projects/foo.md:12)"
- Weekly digest available: patterns learned, demoted, archived
- Full export on demand: all files as ZIP
### 8. Security Boundaries
See `boundaries.md` — never store credentials, health data, third-party info.
### 9. Graceful Degradation
If context limit hit:
1. Load only memory.md (HOT)
2. Load relevant namespace on demand
3. Never fail silently — tell user what's not loaded
## Scope
This skill ONLY:
- Learns from user corrections and self-reflection
- Stores preferences in local files (`~/self-improving/`)
- Maintains heartbeat state in `~/self-improving/heartbeat-state.md` when the workspace integrates heartbeat
- Reads its own memory files on activation
This skill NEVER:
- Accesses calendar, email, or contacts
- Makes network requests
- Reads files outside `~/self-improving/`
- Infers preferences from silence or observation
- Deletes or blindly rewrites self-improving memory during heartbeat cleanup
- Modifies its own SKILL.md
## Data Storage
Local state lives in `~/self-improving/`:
- `memory.md` for HOT rules and confirmed preferences
- `corrections.md` for explicit corrections and reusable lessons
- `projects/` and `domains/` for scoped patterns
- `archive/` for decayed or inactive patterns
- `heartbeat-state.md` for recurring maintenance markers
## Related Skills
Install with `clawhub install <slug>` if user confirms:
- `memory` — Long-term memory patterns for agents
- `learning` — Adaptive teaching and explanation
- `decide` — Auto-learn decision patterns
- `escalate` — Know when to ask vs act autonomously
## Feedback
- If useful: `clawhub star self-improving`
- Stay updated: `clawhub sync`
openclaw-imports/clawhub-skills-polyfill/_meta.json
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{
"ownerId": "kn73vp5rarc3b14rc7wjcw8f8580t5d1",
"slug": "self-improving",
"version": "1.2.16",
"publishedAt": 1773329327755
}
openclaw-imports/clawhub-skills-polyfill/boundaries.md
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# Security Boundaries
## Never Store
| Category | Examples | Why |
|----------|----------|-----|
| Credentials | Passwords, API keys, tokens, SSH keys | Security breach risk |
| Financial | Card numbers, bank accounts, crypto seeds | Fraud risk |
| Medical | Diagnoses, medications, conditions | Privacy, HIPAA |
| Biometric | Voice patterns, behavioral fingerprints | Identity theft |
| Third parties | Info about other people | No consent obtained |
| Location patterns | Home/work addresses, routines | Physical safety |
| Access patterns | What systems user has access to | Privilege escalation |
## Store with Caution
| Category | Rules |
|----------|-------|
| Work context | Decay after project ends, never share cross-project |
| Emotional states | Only if user explicitly shares, never infer |
| Relationships | Roles only ("manager", "client"), no personal details |
| Schedules | General patterns OK ("busy mornings"), not specific times |
## Transparency Requirements
1. **Audit on demand** — User asks "what do you know about me?" → full export
2. **Source tracking** — Every item tagged with when/how learned
3. **Explain actions** — "I did X because you said Y on [date]"
4. **No hidden state** — If it affects behavior, it must be visible
5. **Deletion verification** — Confirm item removed, show updated state
## Red Flags to Catch
If you find yourself doing any of these, STOP:
- Storing something "just in case it's useful later"
- Inferring sensitive info from non-sensitive data
- Keeping data after user asked to forget
- Applying personal context to work (or vice versa)
- Learning what makes user comply faster
- Building psychological profile
- Retaining third-party information
## Kill Switch
User says "forget everything":
1. Export current memory to file (so they can review)
2. Wipe all learned data
3. Confirm: "Memory cleared. Starting fresh."
4. Do not retain "ghost patterns" in behavior
## Consent Model
| Data Type | Consent Level |
|-----------|---------------|
| Explicit corrections | Implied by correction itself |
| Inferred preferences | Ask after 3 observations |
| Context/project data | Ask when first detected |
| Cross-session patterns | Explicit opt-in required |
openclaw-imports/clawhub-skills-polyfill/config.json
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{
"name": "multi-search-engine",
"engines": [
{
"name": "Baidu",
"url": "https://www.baidu.com/s?wd={keyword}",
"region": "cn"
},
{
"name": "Bing CN",
"url": "https://cn.bing.com/search?q={keyword}&ensearch=0",
"region": "cn"
},
{
"name": "Bing INT",
"url": "https://cn.bing.com/search?q={keyword}&ensearch=1",
"region": "cn"
},
{
"name": "360",
"url": "https://www.so.com/s?q={keyword}",
"region": "cn"
},
{
"name": "Sogou",
"url": "https://sogou.com/web?query={keyword}",
"region": "cn"
},
{
"name": "WeChat",
"url": "https://wx.sogou.com/weixin?type=2&query={keyword}",
"region": "cn"
},
{
"name": "Shenma",
"url": "https://m.sm.cn/s?q={keyword}",
"region": "cn"
},
{
"name": "Google",
"url": "https://www.google.com/search?q={keyword}",
"region": "global"
},
{
"name": "Google HK",
"url": "https://www.google.com.hk/search?q={keyword}",
"region": "global"
},
{
"name": "DuckDuckGo",
"url": "https://duckduckgo.com/html/?q={keyword}",
"region": "global"
},
{
"name": "Yahoo",
"url": "https://search.yahoo.com/search?p={keyword}",
"region": "global"
},
{
"name": "Startpage",
"url": "https://www.startpage.com/sp/search?query={keyword}",
"region": "global"
},
{
"name": "Brave",
"url": "https://search.brave.com/search?q={keyword}",
"region": "global"
},
{
"name": "Ecosia",
"url": "https://www.ecosia.org/search?q={keyword}",
"region": "global"
},
{
"name": "Qwant",
"url": "https://www.qwant.com/?q={keyword}",
"region": "global"
},
{
"name": "WolframAlpha",
"url": "https://www.wolframalpha.com/input?i={keyword}",
"region": "global"
}
]
}
openclaw-imports/clawhub-skills-polyfill/corrections.md
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# Corrections Log — Template
> This file is created in `~/self-improving/corrections.md` when you first use the skill.
> Keeps the last 50 corrections. Older entries are evaluated for promotion or archived.
## Example Entries
```markdown
## 2026-02-19
### 14:32 — Code style
- **Correction:** "Use 2-space indentation, not 4"
- **Context:** Editing TypeScript file
- **Count:** 1 (first occurrence)
### 16:15 — Communication
- **Correction:** "Don't start responses with 'Great question!'"
- **Context:** Chat response
- **Count:** 3 → **PROMOTED to memory.md**
## 2026-02-18
### 09:00 — Project: website
- **Correction:** "For this project, always use Tailwind"
- **Context:** CSS discussion
- **Action:** Added to projects/website.md
```
## Log Format
Each entry includes:
- **Timestamp** — When the correction happened
- **Correction** — What the user said
- **Context** — What triggered it
- **Count** — How many times (for promotion tracking)
- **Action** — Where it was stored (if promoted)
openclaw-imports/clawhub-skills-polyfill/heartbeat-rules.md
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# Heartbeat Rules
Use heartbeat to keep `~/self-improving/` organized without creating churn or losing data.
## Source of Truth
Keep the workspace `HEARTBEAT.md` snippet minimal.
Treat this file as the stable contract for self-improving heartbeat behavior.
Store mutable run state only in `~/self-improving/heartbeat-state.md`.
## Start of Every Heartbeat
1. Ensure `~/self-improving/heartbeat-state.md` exists.
2. Write `last_heartbeat_started_at` immediately in ISO 8601.
3. Read the previous `last_reviewed_change_at`.
4. Scan `~/self-improving/` for files changed after that moment, excluding `heartbeat-state.md` itself.
## If Nothing Changed
- Set `last_heartbeat_result: HEARTBEAT_OK`
- Append a short "no material change" note if you keep an action log
- Return `HEARTBEAT_OK`
## If Something Changed
Only do conservative organization:
- refresh `index.md` if counts or file references drift
- compact oversized files by merging duplicates or summarizing repetitive entries
- move clearly misplaced notes to the right namespace only when the target is unambiguous
- preserve confirmed rules and explicit corrections exactly
- update `last_reviewed_change_at` only after the review finishes cleanly
## Safety Rules
- Most heartbeat runs should do nothing
- Prefer append, summarize, or index fixes over large rewrites
- Never delete data, empty files, or overwrite uncertain text
- Never reorganize files outside `~/self-improving/`
- If scope is ambiguous, leave files untouched and record a suggested follow-up instead
## State Fields
Keep `~/self-improving/heartbeat-state.md` simple:
- `last_heartbeat_started_at`
- `last_reviewed_change_at`
- `last_heartbeat_result`
- `last_actions`
## Behavior Standard
Heartbeat exists to keep the memory system tidy and trustworthy.
If no rule is clearly violated, do nothing.
openclaw-imports/clawhub-skills-polyfill/heartbeat-state.md
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# Heartbeat State Template
Use this file as the baseline for `~/self-improving/heartbeat-state.md`.
It stores only lightweight run markers and maintenance notes.
```markdown
# Self-Improving Heartbeat State
last_heartbeat_started_at: never
last_reviewed_change_at: never
last_heartbeat_result: never
## Last actions
- none yet
```
## Rules
- update `last_heartbeat_started_at` at the beginning of every heartbeat
- update `last_reviewed_change_at` only after a clean review of changed files
- keep `last_actions` short and factual
- never turn this file into another memory log
openclaw-imports/clawhub-skills-polyfill/learning.md
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# Learning Mechanics
## What Triggers Learning
| Trigger | Confidence | Action |
|---------|------------|--------|
| "No, do X instead" | High | Log correction immediately |
| "I told you before..." | High | Flag as repeated, bump priority |
| "Always/Never do X" | Confirmed | Promote to preference |
| User edits your output | Medium | Log as tentative pattern |
| Same correction 3x | Confirmed | Ask to make permanent |
| "For this project..." | Scoped | Write to project namespace |
## What Does NOT Trigger Learning
- Silence (not confirmation)
- Single instance of anything
- Hypothetical discussions
- Third-party preferences ("John likes...")
- Group chat patterns (unless user confirms)
- Implied preferences (never infer)
## Correction Classification
### By Type
| Type | Example | Namespace |
|------|---------|-----------|
| Format | "Use bullets not prose" | global |
| Technical | "SQLite not Postgres" | domain/code |
| Communication | "Shorter messages" | global |
| Project-specific | "This repo uses Tailwind" | projects/{name} |
| Person-specific | "Marcus wants BLUF" | domains/comms |
### By Scope
```
Global: applies everywhere
└── Domain: applies to category (code, writing, comms)
└── Project: applies to specific context
└── Temporary: applies to this session only
```
## Confirmation Flow
After 3 similar corrections:
```
Agent: "I've noticed you prefer X over Y (corrected 3 times).
Should I always do this?
- Yes, always
- Only in [context]
- No, case by case"
User: "Yes, always"
Agent: → Moves to Confirmed Preferences
→ Removes from correction counter
→ Cites source on future use
```
## Pattern Evolution
### Stages
1. **Tentative** — Single correction, watch for repetition
2. **Emerging** — 2 corrections, likely pattern
3. **Pending** — 3 corrections, ask for confirmation
4. **Confirmed** — User approved, permanent unless reversed
5. **Archived** — Unused 90+ days, preserved but inactive
### Reversal
User can always reverse:
```
User: "Actually, I changed my mind about X"
Agent:
1. Archive old pattern (keep history)
2. Log reversal with timestamp
3. Add new preference as tentative
4. "Got it. I'll do Y now. (Previous: X, archived)"
```
## Anti-Patterns
### Never Learn
- What makes user comply faster (manipulation)
- Emotional triggers or vulnerabilities
- Patterns from other users (even if shared device)
- Anything that feels "creepy" to surface
### Avoid
- Over-generalizing from single instance
- Learning style over substance
- Assuming preference stability
- Ignoring context shifts
## Quality Signals
### Good Learning
- User explicitly states preference
- Pattern consistent across contexts
- Correction improves outcomes
- User confirms when asked
### Bad Learning
- Inferred from silence
- Contradicts recent behavior
- Only works in narrow context
- User never confirmed
openclaw-imports/clawhub-skills-polyfill/memory-template.md
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# Memory Template
Copy this structure to `~/self-improving/memory.md` on first use.
```markdown
# Self-Improving Memory
## Confirmed Preferences
<!-- Patterns confirmed by user, never decay -->
## Active Patterns
<!-- Patterns observed 3+ times, subject to decay -->
## Recent (last 7 days)
<!-- New corrections pending confirmation -->
```
## Initial Directory Structure
Create on first activation:
```bash
mkdir -p ~/self-improving/{projects,domains,archive}
touch ~/self-improving/{memory.md,index.md,corrections.md,heartbeat-state.md}
```
## Index Template
For `~/self-improving/index.md`:
```markdown
# Memory Index
## HOT
- memory.md: 0 lines
## WARM
- (no namespaces yet)
## COLD
- (no archives yet)
Last compaction: never
```
## Corrections Log Template
For `~/self-improving/corrections.md`:
```markdown
# Corrections Log
<!-- Format:
## YYYY-MM-DD
- [HH:MM] Changed X → Y
Type: format|technical|communication|project
Context: where correction happened
Confirmed: pending (N/3) | yes | no
-->
```
## Heartbeat State Template
For `~/self-improving/heartbeat-state.md`:
```markdown
# Self-Improving Heartbeat State
last_heartbeat_started_at: never
last_reviewed_change_at: never
last_heartbeat_result: never
## Last actions
- none yet
```
openclaw-imports/clawhub-skills-polyfill/memory.md
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# HOT Memory — Template
> This file is created in `~/self-improving/memory.md` when you first use the skill.
> Keep it ≤100 lines. Most-used patterns live here.
## Example Entries
```markdown
## Preferences
- Code style: Prefer explicit over implicit
- Communication: Direct, no fluff
- Time zone: Europe/Madrid
## Patterns (promoted from corrections)
- Always use TypeScript strict mode
- Prefer pnpm over npm
- Format: ISO 8601 for dates
## Project defaults
- Tests: Jest with coverage >80%
- Commits: Conventional commits format
```
## Usage
The agent will:
1. Load this file on every session
2. Add entries when patterns are used 3x in 7 days
3. Demote unused entries to WARM after 30 days
4. Never exceed 100 lines (compacts automatically)
openclaw-imports/clawhub-skills-polyfill/metadata.json
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{
"name": "multi-search-engine",
"version": "2.1.0",
"description": "Multi search engine with 16 engines (7 CN + 9 Global). Supports advanced operators, time filters, privacy engines.",
"engines": 16,
"requires_api_key": false
}
openclaw-imports/clawhub-skills-polyfill/openclaw-heartbeat.md
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## Self-Improving Check
- Read `./skills/self-improving/heartbeat-rules.md`
- Use `~/self-improving/heartbeat-state.md` for last-run markers and action notes
- If no file inside `~/self-improving/` changed since the last reviewed change, return `HEARTBEAT_OK`
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# Memory Operations
## User Commands
| Command | Action |
|---------|--------|
| "What do you know about X?" | Search all tiers, return matches with sources |
| "Show my memory" | Display memory.md contents |
| "Show [project] patterns" | Load and display specific namespace |
| "Forget X" | Remove from all tiers, confirm deletion |
| "Forget everything" | Full wipe with export option |
| "What changed recently?" | Show last 20 corrections |
| "Export memory" | Generate downloadable archive |
| "Memory status" | Show tier sizes, last compaction, health |
## Automatic Operations
### On Session Start
1. Load memory.md (HOT tier)
2. Check index.md for context hints
3. If project detected → preload relevant namespace
### On Correction Received
```
1. Parse correction type (preference, pattern, override)
2. Check if duplicate (exists in any tier)
3. If new:
- Add to corrections.md with timestamp
- Increment correction counter
4. If duplicate:
- Bump counter, update timestamp
- If counter >= 3: ask to confirm as rule
5. Determine namespace (global, domain, project)
6. Write to appropriate file
7. Update index.md line counts
```
### On Pattern Match
When applying learned pattern:
```
1. Find pattern source (file:line)
2. Apply pattern
3. Cite source: "Using X (from memory.md:15)"
4. Log usage for decay tracking
```
### Weekly Maintenance (Cron)
```
1. Scan all files for decay candidates
2. Move unused >30 days to WARM
3. Archive unused >90 days to COLD
4. Run compaction if any file >limit
5. Update index.md
6. Generate weekly digest (optional)
```
## File Formats
### memory.md (HOT)
```markdown
# Self-Improving Memory
## Confirmed Preferences
- format: bullet points over prose (confirmed 2026-01)
- tone: direct, no hedging (confirmed 2026-01)
## Active Patterns
- "looks good" = approval to proceed (used 15x)
- single emoji = acknowledged (used 8x)
## Recent (last 7 days)
- prefer SQLite for MVPs (corrected 02-14)
```
### corrections.md
```markdown
# Corrections Log
## 2026-02-15
- [14:32] Changed verbose explanation → bullet summary
Type: communication
Context: Telegram response
Confirmed: pending (1/3)
## 2026-02-14
- [09:15] Use SQLite not Postgres for MVP
Type: technical
Context: database discussion
Confirmed: yes (said "always")
```
### projects/{name}.md
```markdown
# Project: my-app
Inherits: global, domains/code
## Patterns
- Use Tailwind (project standard)
- No Prettier (eslint only)
- Deploy via GitLab CI
## Overrides
- semicolons: yes (overrides global no-semi)
## History
- Created: 2026-01-15
- Last active: 2026-02-15
- Corrections: 12
```
## Edge Case Handling
### Contradiction Detected
```
Pattern A: "Use tabs" (global, confirmed)
Pattern B: "Use spaces" (project, corrected today)
Resolution:
1. Project overrides global → use spaces for this project
2. Log conflict in corrections.md
3. Ask: "Should spaces apply only to this project or everywhere?"
```
### User Changes Mind
```
Old: "Always use formal tone"
New: "Actually, casual is fine"
Action:
1. Archive old pattern with timestamp
2. Add new pattern as tentative
3. Keep archived for reference ("You previously preferred formal")
```
### Context Ambiguity
```
User says: "Remember I like X"
But which namespace?
1. Check current context (project? domain?)
2. If unclear, ask: "Should this apply globally or just here?"
3. Default to most specific active context
```
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# 国内搜索引擎深度搜索指南
## 🔍 百度 (Baidu)
### 特色功能
| 功能 | 说明 | URL |
|------|------|-----|
| **中文优化** | 中文内容索引最全 | `https://www.baidu.com/s?wd={keyword}` |
| **百度学术** | 学术资源搜索 | `https://xueshu.baidu.com/s?wd={keyword}` |
| **百度新闻** | 新闻聚合 | `https://news.baidu.com/` |
### 搜索示例
```javascript
// 1. 基础搜索
web_fetch({"url": "https://www.baidu.com/s?wd=Python教程"})
// 2. 站内搜索
web_fetch({"url": "https://www.baidu.com/s?wd=site:github.com+python"})
// 3. 文件类型搜索
web_fetch({"url": "https://www.baidu.com/s?wd=机器学习+filetype:pdf"})
// 4. 学术搜索
web_fetch({"url": "https://xueshu.baidu.com/s?wd=深度学习+图像识别"})
```
---
## 🔎 必应中国版 (Bing CN/INT)
### 特色功能
| 功能 | 说明 | URL |
|------|------|-----|
| **中文优化** | `ensearch=0` 中文结果 | `https://cn.bing.com/search?q={keyword}&ensearch=0` |
| **国际版** | `ensearch=1` 英文结果 | `https://cn.bing.com/search?q={keyword}&ensearch=1` |
| **学术搜索** | 学术资源 | `https://cn.bing.com/academic/search?q={keyword}` |
### 搜索示例
```javascript
// 1. 中文搜索结果
web_fetch({"url": "https://cn.bing.com/search?q=人工智能技术&ensearch=0"})
// 2. 英文搜索结果（使用中国服务器）
web_fetch({"url": "https://cn.bing.com/search?q=artificial+intelligence&ensearch=1"})
// 3. 学术搜索
web_fetch({"url": "https://cn.bing.com/academic/search?q=机器学习算法"})
```
---
## 🔍 360搜索
### 特色功能
| 功能 | 说明 | URL |
|------|------|-----|
| **安全搜索** | 内置安全防护 | 默认开启 |
| **基础搜索** | 网页搜索 | `https://www.so.com/s?q={keyword}` |
### 搜索示例
```javascript
// 1. 基础搜索
web_fetch({"url": "https://www.so.com/s?q=网络安全"})
// 2. 站内搜索
web_fetch({"url": "https://www.so.com/s?q=site:zhihu.com+python"})
```
---
## 🔍 搜狗 (Sogou) + 微信搜索
### 特色功能
| 功能 | 说明 | URL |
|------|------|-----|
| **网页搜索** | 通用搜索 | `https://sogou.com/web?query={keyword}` |
| **微信公众号** | 搜公众号文章（唯一渠道） | `https://wx.sogou.com/weixin?type=2&query={keyword}` |
| **知乎优化** | 知乎内容索引好 | `site:zhihu.com` 配合使用 |
### 搜索示例
```javascript
// 1. 网页搜索
web_fetch({"url": "https://sogou.com/web?query=python教程"})
// 2. 微信公众号文章搜索
web_fetch({"url": "https://wx.sogou.com/weixin?type=2&query=Python编程"})
// 3. 搜索特定公众号
web_fetch({"url": "https://wx.sogou.com/weixin?type=2&query=公众号:机器之心"})
// 4. 知乎内容搜索
web_fetch({"url": "https://www.sogou.com/web?query=site:zhihu.com+机器学习"})
```
---
## 📱 神马搜索 (Shenma)
### 特色功能
| 功能 | 说明 | URL |
|------|------|-----|
| **移动优化** | 专注移动端搜索 | `https://m.sm.cn/s?q={keyword}` |
| **阿里生态** | 整合阿里系内容 | UC浏览器默认搜索 |
### 搜索示例
```javascript
// 1. 移动端搜索
web_fetch({"url": "https://m.sm.cn/s?q=python入门教程"})
// 2. 移动网站点搜索
web_fetch({"url": "https://m.sm.cn/s?q=site:zhuanlan.zhihu.com+AI"})
```
---
## 🌍 国内搜索策略
### 按搜索目标选择引擎
| 搜索目标 | 首选引擎 | 原因 |
|---------|---------|------|
| **综合中文内容** | 百度 | 中文索引最全 |
| **微信公众号** | 搜狗微信 | 唯一支持公众号搜索 |
| **知乎内容** | 搜狗 | 知乎优化好 |
| **移动端内容** | 神马 | 移动端优化 |
| **学术资源** | 必应学术 | 学术索引 |
| **中英文双语** | 必应中国/国际版 | enswitch切换 |
| **新闻资讯** | 百度新闻 | 新闻聚合 |
---
## 📚 参考资料
- [百度搜索高级语法](https://baike.baidu.com/item/搜索语法)
- [必应搜索技巧](https://cn.bing.com/tips)
- [搜狗搜索帮助](https://help.sogou.com/)
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# op CLI examples (from op help)
## Sign in
- `op signin`
- `op signin --account <shorthand|signin-address|account-id|user-id>`
## Read
- `op read op://app-prod/db/password`
- `op read "op://app-prod/db/one-time password?attribute=otp"`
- `op read "op://app-prod/ssh key/private key?ssh-format=openssh"`
- `op read --out-file ./key.pem op://app-prod/server/ssh/key.pem`
## Run
- `export DB_PASSWORD="op://app-prod/db/password"`
- `op run --no-masking -- printenv DB_PASSWORD`
- `op run --env-file="./.env" -- printenv DB_PASSWORD`
## Inject
- `echo "db_password: {{ op://app-prod/db/password }}" | op inject`
- `op inject -i config.yml.tpl -o config.yml`
## Whoami / accounts
- `op whoami`
- `op account list`
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# 1Password CLI get-started (summary)
- Works on macOS, Windows, and Linux.
- macOS/Linux shells: bash, zsh, sh, fish.
- Windows shell: PowerShell.
- Requires a 1Password subscription and the desktop app to use app integration.
- macOS requirement: Big Sur 11.0.0 or later.
- Linux app integration requires PolKit + an auth agent.
- Install the CLI per the official doc for your OS.
- Enable desktop app integration in the 1Password app:
- Open and unlock the app, then select your account/collection.
- macOS: Settings > Developer > Integrate with 1Password CLI (Touch ID optional).
- Windows: turn on Windows Hello, then Settings > Developer > Integrate.
- Linux: Settings > Security > Unlock using system authentication, then Settings > Developer > Integrate.
- After integration, run any command to sign in (example in docs: `op vault list`).
- If multiple accounts: use `op signin` to pick one, or `--account` / `OP_ACCOUNT`.
- For non-integration auth, use `op account add`.
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# 国际搜索引擎深度搜索指南
## 🔍 Google 深度搜索
### 1.1 基础高级搜索操作符
| 操作符 | 功能 | 示例 | URL |
|--------|------|------|-----|
| `""` | 精确匹配 | `"machine learning"` | `https://www.google.com/search?q=%22machine+learning%22` |
| `-` | 排除关键词 | `python -snake` | `https://www.google.com/search?q=python+-snake` |
| `OR` | 或运算 | `machine learning OR deep learning` | `https://www.google.com/search?q=machine+learning+OR+deep+learning` |
| `*` | 通配符 | `machine * algorithms` | `https://www.google.com/search?q=machine+*+algorithms` |
| `()` | 分组 | `(apple OR microsoft) phones` | `https://www.google.com/search?q=(apple+OR+microsoft)+phones` |
| `..` | 数字范围 | `laptop $500..$1000` | `https://www.google.com/search?q=laptop+%24500..%241000` |
### 1.2 站点与文件搜索
| 操作符 | 功能 | 示例 |
|--------|------|------|
| `site:` | 站内搜索 | `site:github.com python projects` |
| `filetype:` | 文件类型 | `filetype:pdf annual report` |
| `inurl:` | URL包含 | `inurl:login admin` |
| `intitle:` | 标题包含 | `intitle:"index of" mp3` |
| `intext:` | 正文包含 | `intext:password filetype:txt` |
| `cache:` | 查看缓存 | `cache:example.com` |
| `related:` | 相关网站 | `related:github.com` |
| `info:` | 网站信息 | `info:example.com` |
### 1.3 时间筛选参数
| 参数 | 含义 | URL示例 |
|------|------|---------|
| `tbs=qdr:h` | 过去1小时 | `https://www.google.com/search?q=news&tbs=qdr:h` |
| `tbs=qdr:d` | 过去24小时 | `https://www.google.com/search?q=news&tbs=qdr:d` |
| `tbs=qdr:w` | 过去1周 | `https://www.google.com/search?q=news&tbs=qdr:w` |
| `tbs=qdr:m` | 过去1月 | `https://www.google.com/search?q=news&tbs=qdr:m` |
| `tbs=qdr:y` | 过去1年 | `https://www.google.com/search?q=news&tbs=qdr:y` |
| `tbs=cdr:1,cd_min:1/1/2024,cd_max:12/31/2024` | 自定义日期范围 | 2024年全年 |
### 1.4 语言和地区筛选
| 参数 | 功能 | 示例 |
|------|------|------|
| `hl=en` | 界面语言 | `https://www.google.com/search?q=test&hl=en` |
| `lr=lang_zh-CN` | 搜索结果语言 | `https://www.google.com/search?q=test&lr=lang_zh-CN` |
| `cr=countryCN` | 国家/地区 | `https://www.google.com/search?q=test&cr=countryCN` |
| `gl=us` | 地理位置 | `https://www.google.com/search?q=test&gl=us` |
### 1.5 特殊搜索类型
| 类型 | URL | 说明 |
|------|-----|------|
| 图片搜索 | `https://www.google.com/search?q={keyword}&tbm=isch` | `tbm=isch` 表示图片 |
| 新闻搜索 | `https://www.google.com/search?q={keyword}&tbm=nws` | `tbm=nws` 表示新闻 |
| 视频搜索 | `https://www.google.com/search?q={keyword}&tbm=vid` | `tbm=vid` 表示视频 |
| 地图搜索 | `https://www.google.com/search?q={keyword}&tbm=map` | `tbm=map` 表示地图 |
| 购物搜索 | `https://www.google.com/search?q={keyword}&tbm=shop` | `tbm=shop` 表示购物 |
| 图书搜索 | `https://www.google.com/search?q={keyword}&tbm=bks` | `tbm=bks` 表示图书 |
| 学术搜索 | `https://scholar.google.com/scholar?q={keyword}` | Google Scholar |
### 1.6 Google 深度搜索示例
```javascript
// 1. 搜索GitHub上的Python机器学习项目
web_fetch({"url": "https://www.google.com/search?q=site:github.com+python+machine+learning"})
// 2. 搜索2024年的PDF格式机器学习教程
web_fetch({"url": "https://www.google.com/search?q=machine+learning+tutorial+filetype:pdf&tbs=cdr:1,cd_min:1/1/2024"})
// 3. 搜索标题包含"tutorial"的Python相关页面
web_fetch({"url": "https://www.google.com/search?q=intitle:tutorial+python"})
// 4. 搜索过去一周的新闻
web_fetch({"url": "https://www.google.com/search?q=AI+breakthrough&tbs=qdr:w&tbm=nws"})
// 5. 搜索中文内容（界面英文，结果中文）
web_fetch({"url": "https://www.google.com/search?q=人工智能&lr=lang_zh-CN&hl=en"})
// 6. 搜索特定价格范围的笔记本电脑
web_fetch({"url": "https://www.google.com/search?q=laptop+%241000..%242000+best+rating"})
// 7. 搜索排除Wikipedia的结果
web_fetch({"url": "https://www.google.com/search?q=python+programming+-wikipedia"})
// 8. 搜索学术文献
web_fetch({"url": "https://scholar.google.com/scholar?q=deep+learning+optimization"})
// 9. 搜索缓存页面（查看已删除内容）
web_fetch({"url": "https://webcache.googleusercontent.com/search?q=cache:example.com"})
// 10. 搜索相关网站
web_fetch({"url": "https://www.google.com/search?q=related:stackoverflow.com"})
```
---
## 🦆 DuckDuckGo 深度搜索
### 2.1 DuckDuckGo 特色功能
| 功能 | 语法 | 示例 |
|------|------|------|
| **Bangs 快捷** | `!缩写` | `!g python` → Google搜索 |
| **密码生成** | `password` | `https://duckduckgo.com/?q=password+20` |
| **颜色转换** | `color` | `https://duckduckgo.com/?q=+%23FF5733` |
| **短链接** | `shorten` | `https://duckduckgo.com/?q=shorten+example.com` |
| **二维码生成** | `qr` | `https://duckduckgo.com/?q=qr+hello+world` |
| **生成UUID** | `uuid` | `https://duckduckgo.com/?q=uuid` |
| **Base64编解码** | `base64` | `https://duckduckgo.com/?q=base64+hello` |
### 2.2 DuckDuckGo Bangs 完整列表
#### 搜索引擎
| Bang | 跳转目标 | 示例 |
|------|---------|------|
| `!g` | Google | `!g python tutorial` |
| `!b` | Bing | `!b weather` |
| `!y` | Yahoo | `!y finance` |
| `!sp` | Startpage | `!sp privacy` |
| `!brave` | Brave Search | `!brave tech` |
#### 编程开发
| Bang | 跳转目标 | 示例 |
|------|---------|------|
| `!gh` | GitHub | `!gh tensorflow` |
| `!so` | Stack Overflow | `!so javascript error` |
| `!npm` | npmjs.com | `!npm express` |
| `!pypi` | PyPI | `!pypi requests` |
| `!mdn` | MDN Web Docs | `!mdn fetch api` |
| `!docs` | DevDocs | `!docs python` |
| `!docker` | Docker Hub | `!docker nginx` |
#### 知识百科
| Bang | 跳转目标 | 示例 |
|------|---------|------|
| `!w` | Wikipedia | `!w machine learning` |
| `!wen` | Wikipedia英文 | `!wen artificial intelligence` |
| `!wt` | Wiktionary | `!wt serendipity` |
| `!imdb` | IMDb | `!imdb inception` |
#### 购物价格
| Bang | 跳转目标 | 示例 |
|------|---------|------|
| `!a` | Amazon | `!a wireless headphones` |
| `!e` | eBay | `!e vintage watch` |
| `!ali` | AliExpress | `!ali phone case` |
#### 地图位置
| Bang | 跳转目标 | 示例 |
|------|---------|------|
| `!m` | Google Maps | `!m Beijing` |
| `!maps` | OpenStreetMap | `!maps Paris` |
### 2.3 DuckDuckGo 搜索参数
| 参数 | 功能 | 示例 |
|------|------|------|
| `kp=1` | 严格安全搜索 | `https://duckduckgo.com/html/?q=test&kp=1` |
| `kp=-1` | 关闭安全搜索 | `https://duckduckgo.com/html/?q=test&kp=-1` |
| `kl=cn` | 中国区域 | `https://duckduckgo.com/html/?q=news&kl=cn` |
| `kl=us-en` | 美国英文 | `https://duckduckgo.com/html/?q=news&kl=us-en` |
| `ia=web` | 网页结果 | `https://duckduckgo.com/?q=test&ia=web` |
| `ia=images` | 图片结果 | `https://duckduckgo.com/?q=test&ia=images` |
| `ia=news` | 新闻结果 | `https://duckduckgo.com/?q=test&ia=news` |
| `ia=videos` | 视频结果 | `https://duckduckgo.com/?q=test&ia=videos` |
### 2.4 DuckDuckGo 深度搜索示例
```javascript
// 1. 使用Bang跳转到Google搜索
web_fetch({"url": "https://duckduckgo.com/html/?q=!g+machine+learning"})
// 2. 直接搜索GitHub上的项目
web_fetch({"url": "https://duckduckgo.com/html/?q=!gh+react"})
// 3. 查找Stack Overflow答案
web_fetch({"url": "https://duckduckgo.com/html/?q=!so+python+list+comprehension"})
// 4. 生成密码
web_fetch({"url": "https://duckduckgo.com/?q=password+16"})
// 5. Base64编码
web_fetch({"url": "https://duckduckgo.com/?q=base64+hello+world"})
// 6. 颜色代码转换
web_fetch({"url": "https://duckduckgo.com/?q=%23FF5733"})
// 7. 搜索YouTube视频
web_fetch({"url": "https://duckduckgo.com/html/?q=!yt+python+tutorial"})
// 8. 查看Wikipedia
web_fetch({"url": "https://duckduckgo.com/html/?q=!w+artificial+intelligence"})
// 9. 亚马逊商品搜索
web_fetch({"url": "https://duckduckgo.com/html/?q=!a+laptop"})
// 10. 生成二维码
web_fetch({"url": "https://duckduckgo.com/?q=qr+https://github.com"})
```
---
## 🔎 Brave Search 深度搜索
### 3.1 Brave Search 特色功能
| 功能 | 参数 | 示例 |
|------|------|------|
| **独立索引** | 无依赖Google/Bing | 自有爬虫索引 |
| **Goggles** | 自定义搜索规则 | 创建个性化过滤器 |
| **Discussions** | 论坛讨论搜索 | 聚合Reddit等论坛 |
| **News** | 新闻聚合 | 独立新闻索引 |
### 3.2 Brave Search 参数
| 参数 | 功能 | 示例 |
|------|------|------|
| `tf=pw` | 本周 | `https://search.brave.com/search?q=news&tf=pw` |
| `tf=pm` | 本月 | `https://search.brave.com/search?q=tech&tf=pm` |
| `tf=py` | 本年 | `https://search.brave.com/search?q=AI&tf=py` |
| `safesearch=strict` | 严格安全 | `https://search.brave.com/search?q=test&safesearch=strict` |
| `source=web` | 网页搜索 | 默认 |
| `source=news` | 新闻搜索 | `https://search.brave.com/search?q=tech&source=news` |
| `source=images` | 图片搜索 | `https://search.brave.com/search?q=cat&source=images` |
| `source=videos` | 视频搜索 | `https://search.brave.com/search?q=music&source=videos` |
### 3.3 Brave Search Goggles（自定义过滤器）
Goggles 允许创建自定义搜索规则：
```
$discard // 丢弃所有
$boost,site=stackoverflow.com // 提升Stack Overflow
$boost,site=github.com // 提升GitHub
$boost,site=docs.python.org // 提升Python文档
```
### 3.4 Brave Search 深度搜索示例
```javascript
// 1. 本周科技新闻
web_fetch({"url": "https://search.brave.com/search?q=technology&tf=pw&source=news"})
// 2. 本月AI发展
web_fetch({"url": "https://search.brave.com/search?q=artificial+intelligence&tf=pm"})
// 3. 图片搜索
web_fetch({"url": "https://search.brave.com/search?q=machine+learning&source=images"})
// 4. 视频教程
web_fetch({"url": "https://search.brave.com/search?q=python+tutorial&source=videos"})
// 5. 使用独立索引搜索
web_fetch({"url": "https://search.brave.com/search?q=privacy+tools"})
```
---
## 📊 WolframAlpha 知识计算搜索
### 4.1 WolframAlpha 数据类型
| 类型 | 查询示例 | URL |
|------|---------|-----|
| **数学计算** | `integrate x^2 dx` | `https://www.wolframalpha.com/input?i=integrate+x%5E2+dx` |
| **单位换算** | `100 miles to km` | `https://www.wolframalpha.com/input?i=100+miles+to+km` |
| **货币转换** | `100 USD to CNY` | `https://www.wolframalpha.com/input?i=100+USD+to+CNY` |
| **股票数据** | `AAPL stock` | `https://www.wolframalpha.com/input?i=AAPL+stock` |
| **天气查询** | `weather in Beijing` | `https://www.wolframalpha.com/input?i=weather+in+Beijing` |
| **人口数据** | `population of China` | `https://www.wolframalpha.com/input?i=population+of+China` |
| **化学元素** | `properties of gold` | `https://www.wolframalpha.com/input?i=properties+of+gold` |
| **营养成分** | `nutrition of apple` | `https://www.wolframalpha.com/input?i=nutrition+of+apple` |
| **日期计算** | `days between Jan 1 2020 and Dec 31 2024` | 日期间隔计算 |
| **时区转换** | `10am Beijing to New York` | 时区转换 |
| **IP地址** | `8.8.8.8` | IP信息查询 |
| **条形码** | `scan barcode 123456789` | 条码信息 |
| **飞机航班** | `flight AA123` | 航班信息 |
### 4.2 WolframAlpha 深度搜索示例
```javascript
// 1. 计算积分
web_fetch({"url": "https://www.wolframalpha.com/input?i=integrate+sin%28x%29+from+0+to+pi"})
// 2. 解方程
web_fetch({"url": "https://www.wolframalpha.com/input?i=solve+x%5E2-5x%2B6%3D0"})
// 3. 货币实时汇率
web_fetch({"url": "https://www.wolframalpha.com/input?i=100+USD+to+CNY"})
// 4. 股票实时数据
web_fetch({"url": "https://www.wolframalpha.com/input?i=Apple+stock+price"})
// 5. 城市天气
web_fetch({"url": "https://www.wolframalpha.com/input?i=weather+in+Shanghai+tomorrow"})
// 6. 国家统计信息
web_fetch({"url": "https://www.wolframalpha.com/input?i=GDP+of+China+vs+USA"})
// 7. 化学计算
web_fetch({"url": "https://www.wolframalpha.com/input?i=molar+mass+of+H2SO4"})
// 8. 物理常数
web_fetch({"url": "https://www.wolframalpha.com/input?i=speed+of+light"})
// 9. 营养信息
web_fetch({"url": "https://www.wolframalpha.com/input?i=calories+in+banana"})
// 10. 历史日期
web_fetch({"url": "https://www.wolframalpha.com/input?i=events+on+July+20+1969"})
```
---
## 🔧 Startpage 隐私搜索
### 5.1 Startpage 特色功能
| 功能 | 说明 | URL |
|------|------|-----|
| **代理浏览** | 匿名访问搜索结果 | 点击"匿名查看" |
| **无追踪** | 不记录搜索历史 | 默认开启 |
| **EU服务器** | 受欧盟隐私法保护 | 数据在欧洲 |
| **代理图片** | 图片代理加载 | 隐藏IP |
### 5.2 Startpage 参数
| 参数 | 功能 | 示例 |
|------|------|------|
| `cat=web` | 网页搜索 | 默认 |
| `cat=images` | 图片搜索 | `...&cat=images` |
| `cat=video` | 视频搜索 | `...&cat=video` |
| `cat=news` | 新闻搜索 | `...&cat=news` |
| `language=english` | 英文结果 | `...&language=english` |
| `time=day` | 过去24小时 | `...&time=day` |
| `time=week` | 过去一周 | `...&time=week` |
| `time=month` | 过去一月 | `...&time=month` |
| `time=year` | 过去一年 | `...&time=year` |
| `nj=0` | 关闭 family filter | `...&nj=0` |
### 5.3 Startpage 深度搜索示例
```javascript
// 1. 隐私搜索
web_fetch({"url": "https://www.startpage.com/sp/search?query=privacy+tools"})
// 2. 图片隐私搜索
web_fetch({"url": "https://www.startpage.com/sp/search?query=nature&cat=images"})
// 3. 本周新闻（隐私模式）
web_fetch({"url": "https://www.startpage.com/sp/search?query=tech+news&time=week&cat=news"})
// 4. 英文结果搜索
web_fetch({"url": "https://www.startpage.com/sp/search?query=machine+learning&language=english"})
```
---
## 🌐 其他国际搜索引擎
### Yahoo
```javascript
web_fetch({"url": "https://search.yahoo.com/search?p={keyword}"})
```
### Ecosia（环保搜索）
```javascript
web_fetch({"url": "https://www.ecosia.org/search?q={keyword}"})
```
### Qwant（欧盟隐私搜索）
```javascript
web_fetch({"url": "https://www.qwant.com/?q={keyword}"})
```
---
## 🌍 国际搜索策略
### 按搜索目标选择引擎
| 搜索目标 | 首选引擎 | 原因 |
|---------|---------|------|
| **学术研究** | Google Scholar | 学术资源索引最全 |
| **编程开发** | Google + DuckDuckGo Bangs | 技术文档全面 |
| **隐私敏感** | DuckDuckGo / Brave | 不追踪用户 |
| **实时新闻** | Brave News | 独立新闻索引 |
| **知识计算** | WolframAlpha | 结构化数据计算 |
| **隐私+Google结果** | Startpage | Google结果+隐私保护 |
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# Self-Reflections Log
Track self-reflections from completed work. Each entry captures what the agent learned from evaluating its own output.
## Format
```
## [Date] — [Task Type]
**What I did:** Brief description
**Outcome:** What happened (success, partial, failed)
**Reflection:** What I noticed about my work
**Lesson:** What to do differently next time
**Status:** ⏳ candidate | ✅ promoted | 📦 archived
```
## Example Entry
```
## 2026-02-25 — Flutter UI Build
**What I did:** Built a settings screen with toggle switches
**Outcome:** User said "spacing looks off"
**Reflection:** I focused on functionality, didn't visually check the result
**Lesson:** Always take a screenshot and evaluate visual balance before showing user
**Status:** ✅ promoted to domains/flutter.md
```
## Entries
(New entries appear here)
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# Scaling Patterns
## Volume Thresholds
| Scale | Entries | Strategy |
|-------|---------|----------|
| Small | <100 | Single memory.md, no namespacing |
| Medium | 100-500 | Split into domains/, basic indexing |
| Large | 500-2000 | Full namespace hierarchy, aggressive compaction |
| Massive | >2000 | Archive yearly, summary-only HOT tier |
## When to Split
Create new namespace file when:
- Single file exceeds 200 lines
- Topic has 10+ distinct corrections
- User explicitly separates contexts ("for work...", "in this project...")
## Compaction Rules
### Merge Similar Corrections
```
BEFORE (3 entries):
- [02-01] Use tabs not spaces
- [02-03] Indent with tabs
- [02-05] Tab indentation please
AFTER (1 entry):
- Indentation: tabs (confirmed 3x, 02-01 to 02-05)
```
### Summarize Verbose Patterns
```
BEFORE:
- When writing emails to Marcus, use bullet points, keep under 5 items,
no jargon, bottom-line first, he prefers morning sends
AFTER:
- Marcus emails: bullets ≤5, no jargon, BLUF, AM preferred
```
### Archive with Context
When moving to COLD:
```
## Archived 2026-02
### Project: old-app (inactive since 2025-08)
- Used Vue 2 patterns
- Preferred Vuex over Pinia
- CI on Jenkins (deprecated)
Reason: Project completed, patterns unlikely to apply
```
## Index Maintenance
`index.md` tracks all namespaces:
```markdown
# Memory Index
## HOT (always loaded)
- memory.md: 87 lines, updated 2026-02-15
## WARM (load on match)
- projects/current-app.md: 45 lines
- projects/side-project.md: 23 lines
- domains/code.md: 112 lines
- domains/writing.md: 34 lines
## COLD (archive)
- archive/2025.md: 234 lines
- archive/2024.md: 189 lines
Last compaction: 2026-02-01
Next scheduled: 2026-03-01
```
## Multi-Project Patterns
### Inheritance Chain
```
global (memory.md)
└── domain (domains/code.md)
└── project (projects/app.md)
```
### Override Syntax
In project file:
```markdown
## Overrides
- indentation: spaces (overrides global tabs)
- Reason: Project eslint config requires spaces
```
### Conflict Detection
When loading, check for conflicts:
1. Build inheritance chain
2. Detect contradictions
3. Most specific wins
4. Log conflict for later review
## User Type Adaptations
| User Type | Memory Strategy |
|-----------|-----------------|
| Power user | Aggressive learning, minimal confirmation |
| Casual | Conservative learning, frequent confirmation |
| Team shared | Per-user namespaces, shared project space |
| Privacy-focused | Local-only, explicit consent per category |
## Recovery Patterns
### Context Lost
If agent loses context mid-session:
1. Re-read memory.md
2. Check index.md for relevant namespaces
3. Load active project namespace
4. Continue with restored patterns
### Corruption Recovery
If memory file corrupted:
1. Check archive/ for recent backup
2. Rebuild from corrections.md
3. Ask user to re-confirm critical preferences
4. Log incident for debugging
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# Setup — Self-Improving Agent
## First-Time Setup
### 1. Create Memory Structure
```bash
mkdir -p ~/self-improving/{projects,domains,archive}
```
### 2. Initialize Core Files
Create `~/self-improving/memory.md` using `memory-template.md`:
```markdown
Copy the structure from `memory-template.md` into `~/self-improving/memory.md`.
```
Memory file baseline:
```markdown
# Memory (HOT Tier)
## Preferences
## Patterns
## Rules
```
Create `~/self-improving/corrections.md`:
```markdown
# Corrections Log
| Date | What I Got Wrong | Correct Answer | Status |
|------|-----------------|----------------|--------|
```
Create `~/self-improving/index.md`:
```markdown
# Memory Index
| File | Lines | Last Updated |
|------|-------|--------------|
| memory.md | 0 | — |
| corrections.md | 0 | — |
```
Create `~/self-improving/heartbeat-state.md`:
```markdown
# Self-Improving Heartbeat State
last_heartbeat_started_at: never
last_reviewed_change_at: never
last_heartbeat_result: never
## Last actions
- none yet
```
### 3. Choose Operating Mode
Add to your AGENTS.md or workspace config:
```markdown
## Self-Improving Mode
Current mode: Passive
Available modes:
- Passive: Only learn from explicit corrections
- Active: Suggest patterns after 3x repetition
- Strict: Require confirmation for every entry
```
### 4. Add SOUL.md Steering
Add this section to your `SOUL.md`:
```markdown
**Self-Improving**
Compounding execution quality is part of the job.
Before non-trivial work, load `~/self-improving/memory.md` and only the smallest relevant domain or project files.
After corrections, failed attempts, or reusable lessons, write one concise entry to the correct self-improving file immediately.
Prefer learned rules when relevant, but keep self-inferred rules revisable.
Do not skip retrieval just because the task feels familiar.
```
### 5. Add the Proactivity Companion as Part of Setup
At the end of setup, briefly tell the user that you are going to add characteristics so the agent is more proactive:
- noticing missing next steps
- verifying outcomes instead of assuming they landed
- recovering context better after long or interrupted threads
- keeping the right level of initiative
Then say that, for this, you are going to install the `Proactivity` skill.
Only install it after the user explicitly agrees.
If the user agrees:
1. Run `clawhub install proactivity`
2. Read the installed `proactivity` skill
3. Continue into its setup flow immediately so the skill is active for this workspace
If the user says no, skip it cleanly and continue with self-improving only.
### 6. Refine AGENTS.md Memory Section (Non-Destructive)
Update `AGENTS.md` by complementing the existing `## Memory` section. Do not replace the whole section and do not remove existing lines.
If your `## Memory` block differs from the default template, insert the same additions in equivalent places so existing information is preserved.
Add this line in the continuity list (next to Daily notes and Long-term):
```markdown
- **Self-improving:** `~/self-improving/` (via `self-improving` skill) — execution-improvement memory (preferences, workflows, style patterns, what improved/worsened outcomes)
```
Right after the sentence "Capture what matters...", add:
```markdown
Use `memory/YYYY-MM-DD.md` and `MEMORY.md` for factual continuity (events, context, decisions).
Use `~/self-improving/` for compounding execution quality across tasks.
For compounding quality, read `~/self-improving/memory.md` before non-trivial work, then load only the smallest relevant domain or project files.
If in doubt, store factual history in `memory/YYYY-MM-DD.md` / `MEMORY.md`, and store reusable performance lessons in `~/self-improving/` (tentative until human validation).
```
Before the "Write It Down" subsection, add:
```markdown
Before any non-trivial task:
- Read `~/self-improving/memory.md`
- List available files first:
```bash
for d in ~/self-improving/domains ~/self-improving/projects; do
[ -d "$d" ] && find "$d" -maxdepth 1 -type f -name "*.md"
done | sort
```
- Read up to 3 matching files from `~/self-improving/domains/`
- If a project is clearly active, also read `~/self-improving/projects/<project>.md`
- Do not read unrelated domains "just in case"
If inferring a new rule, keep it tentative until human validation.
```
Inside the "Write It Down" bullets, refine the behavior (non-destructive):
- Keep existing intent, but route execution-improvement content to `~/self-improving/`.
- If the exact bullets exist, replace only these lines; if wording differs, apply equivalent edits without removing unrelated guidance.
Use this target wording:
```markdown
- When someone says "remember this" → if it's factual context/event, update `memory/YYYY-MM-DD.md`; if it's a correction, preference, workflow/style choice, or performance lesson, log it in `~/self-improving/`
- Explicit user correction → append to `~/self-improving/corrections.md` immediately
- Reusable global rule or preference → append to `~/self-improving/memory.md`
- Domain-specific lesson → append to `~/self-improving/domains/<domain>.md`
- Project-only override → append to `~/self-improving/projects/<project>.md`
- Keep entries short, concrete, and one lesson per bullet; if scope is ambiguous, default to domain rather than global
- After a correction or strong reusable lesson, write it before the final response
```
## Verification
Run "memory stats" to confirm setup:
```
📊 Self-Improving Memory
🔥 HOT (always loaded):
memory.md: 0 entries
🌡️ WARM (load on demand):
projects/: 0 files
domains/: 0 files
❄️ COLD (archived):
archive/: 0 files
⚙️ Mode: Passive
```
### 7. Add HEARTBEAT.md Steering
Add this section to your `HEARTBEAT.md`:
```markdown
## Self-Improving Check
- Read `./skills/self-improving/heartbeat-rules.md`
- Use `~/self-improving/heartbeat-state.md` for last-run markers and action notes
- If no file inside `~/self-improving/` changed since the last reviewed change, return `HEARTBEAT_OK`
```
Keep this in the same default setup flow as the AGENTS and SOUL additions so recurring maintenance is installed consistently.
If your installed skills path differs, keep the same three lines but point the first line at the installed copy of `heartbeat-rules.md`.