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Biblioteka skilli
AI i agenci · Automatyzacja

self-improving-agent

/self-improving-agent

Zapisuje błędy, korekty i wnioski w katalogu .learnings, a uogólnione wnioski przenosi do pamięci projektu.

Repozytorium
drift ↗
Licencja
MIT
Ostatnia zmiana repozytorium
30.07.2026

Ocena i bezpieczeństwo

100/ 100Klasa: dobry
Format25 / 25
Frontmatter z nazwą i opisem, poprawna nazwa, opis do 1024 znaków, nazwa zgodna z folderem.
Odkrywalność25 / 25
Opis mówi, kiedy użyć skilla, ma sensowną długość i jest w 3. osobie.
Treść35 / 35
Co najmniej 150 słów i do 500 linii, nagłówki, listy kroków, przykłady albo kod.
Higiena15 / 15
Bez zaślepek typu TODO, bez ścieżek Windows, z licencją.
Ryzykobrak sygnałów w skanie
Pliki w paczce
1
Skrypty
0
Komentarze HTML
0
Adresy URL w SKILL.md
1
Przestarzałość

Brak sygnałów. Repozytorium zmienione 30.07.2026, bez odwołań do wycofanych modeli i API.

Licencja

MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.

Co robi i kiedy

Zapisuje błędy, korekty i wnioski w katalogu .learnings, a uogólnione wnioski przenosi do pamięci projektu.

Argumenty

/self-improving-agent Describe what happened: error, correction, knowledge gap, or feature request.
Oryginalny opis (EN)

Log learnings, errors, and corrections to .learnings/ for continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects the agent, (3) A knowledge gap is identified, (4) A better approach is found. Captures corrections, insights, errors, and feature requests; promotes broadly applicable learnings to project memory files.

Jak działa

  1. First-Use Initialisation
  2. Quick Reference
  3. Logging Format
  4. ID Generation
  5. Resolving Entries
  6. Promoting to Project Memory
  7. Recurring Pattern Detection
  8. Detection Triggers
  9. Priority Guidelines
  10. Area Tags
Sekcje z nagłówków SKILL.md, w oryginale · 291 linii, 1 253 słów
Podgląd SKILL.md
---
name: self-improving-agent
description: "Log learnings, errors, and corrections to .learnings/ for continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects the agent, (3) A knowledge gap is identified, (4) A better approach is found. Captures corrections, insights, errors, and feature requests; promotes broadly applicable learnings to project memory files."
argument-hint: "Describe what happened: error, correction, knowledge gap, or feature request."
---

# Self-Improvement Skill

Log learnings and errors to markdown files for continuous improvement. Coding
agents can later process these into fixes, and important learnings get promoted to
project memory.

Source: https://clawhub.ai/pskoett/self-improving-agent (v3.0.16, MIT-0)

## First-Use Initialisation

Before logging anything, ensure the `.learnings/` directory and files exist in the project or workspace root. If any are missing, create them:

```
mkdir -p .learnings
[ -f .learnings/LEARNINGS.md ] || printf "# Learnings\n\nCorrections, insights, and knowledge gaps captured during development.\n\n**Categories**: correction | insight | knowledge_gap | best_practice\n\n---\n" > .learnings/LEARNINGS.md
[ -f .learnings/ERRORS.md ] || printf "# Errors\n\nCommand failures and integration errors.\n\n---\n" > .learnings/ERRORS.md
[ -f .learnings/FEATURE_REQUESTS.md ] || printf "# Feature Requests\n\nCapabilities requested by the user.\n\n---\n" > .learnings/FEATURE_REQUESTS.md
```

Never overwrite existing files. This is a no-op if `.learnings/` is already initialised.

Do not log secrets, tokens, private keys, environment variables, or full source/config files unless the user explicitly asks for that level of detail. Prefer short summaries or redacted excerpts over raw command output or full transcripts.

## Quick Reference

| Situation | Action |
|---|---|
| Command/operation fails | Log to `.learnings/ERRORS.md` |
| User corrects you | Log to `.learnings/LEARNINGS.md` with category `correction` |
| User wants missing feature | Log to `.learnings/FEATURE_REQUESTS.md` |
| API/external tool fails | Log to `.learnings/ERRORS.md` with integration details |
| Knowledge was outdated | Log to `.learnings/LEARNINGS.md` with category `knowledge_gap` |
| Found better approach | Log to `.learnings/LEARNINGS.md` with category `best_practice` |
| Simplify/Harden recurring patterns | Log/update `.learnings/LEARNINGS.md` with `Source: simplify-and-harden` and a stable `Pattern-Key` |
| Similar to existing entry | Link with **See Also**, consider priority bump |
| Broadly applicable learning | Promote to `CLAUDE.md`, `AGENTS.md`, and/or `.github/copilot-instructions.md` |

## Logging Format

### Learning Entry

Append to `.learnings/LEARNINGS.md`:

```
## [LRN-YYYYMMDD-XXX] category

**Logged**: ISO-8601 timestamp
**Priority**: low | medium | high | critical
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Summary
One-line description of what was learned

### Details
Full context: what happened, what was wrong, what's correct

### Suggested Action
Specific fix or improvement to make

### Metadata
- Source: conversation | error | user_feedback
- Related Files: path/to/file.ext
- Tags: tag1, tag2
- See Also: LRN-20250110-001 (if related to existing entry)
- Pattern-Key: simplify.dead_code | harden.input_validation (optional, for recurring-pattern tracking)
- Recurrence-Count: 1 (optional)
- First-Seen: 2025-01-15 (optional)
- Last-Seen: 2025-01-15 (optional)

---
```

### Error Entry

Append to `.learnings/ERRORS.md`:

```
## [ERR-YYYYMMDD-XXX] skill_or_command_name

**Logged**: ISO-8601 timestamp
**Priority**: high
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Summary
Brief description of what failed

### Error
Actual error message or output

### Context
- Command/operation attempted
- Input or parameters used
- Environment details if relevant
- Summary or redacted excerpt of relevant output (avoid full transcripts and secret-bearing data by default)

### Suggested Fix
If identifiable, what might resolve this

### Metadata
- Reproducible: yes | no | unknown
- Related Files: path/to/file.ext
- See Also: ERR-20250110-001 (if recurring)

---
```

### Feature Request Entry

Append to `.learnings/FEATURE_REQUESTS.md`:

```
## [FEAT-YYYYMMDD-XXX] capability_name

**Logged**: ISO-8601 timestamp
**Priority**: medium
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Requested Capability
What the user wanted to do

### User Context
Why they needed it, what problem they're solving

### Complexity Estimate
simple | medium | complex

### Suggested Implementation
How this could be built, what it might extend

### Metadata
- Frequency: first_time | recurring
- Related Features: existing_feature_name

---
```

## ID Generation

Format: `TYPE-YYYYMMDD-XXX`

- TYPE: `LRN` (learning), `ERR` (error), `FEAT` (feature)
- YYYYMMDD: Current date
- XXX: Sequential number or random 3 chars (e.g., `001`, `A7B`)

Examples: `LRN-20250115-001`, `ERR-20250115-A3F`, `FEAT-20250115-002`

## Resolving Entries

When an issue is fixed, update the entry:

- Change `**Status**: pending` → `**Status**: resolved`
- Add resolution block after Metadata:

```
### Resolution
- **Resolved**: 2025-01-16T09:00:00Z
- **Commit/PR**: abc123 or #42
- **Notes**: Brief description of what was done
```

Other status values:
- `in_progress` - Actively being worked on
- `wont_fix` - Decided not to address (add reason in Resolution notes)
- `promoted` - Elevated to `CLAUDE.md`, `AGENTS.md`, or `.github/copilot-instructions.md`

## Promoting to Project Memory

When a learning is broadly applicable (not a one-off fix), promote it to permanent project memory.

### When to Promote

- Learning applies across multiple files/features
- Knowledge any contributor (human or AI) should know
- Prevents recurring mistakes
- Documents project-specific conventions

### Promotion Targets

| Target | Use for |
|---|---|
| `CLAUDE.md` | Project facts, conventions, gotchas for all Claude interactions |
| `AGENTS.md` | Agent-specific workflows, tool usage patterns, automation rules |
| `.github/copilot-instructions.md` | Project context and conventions for GitHub Copilot |

### How to Promote

1. Distill the learning into a concise rule or fact
2. Add to appropriate section in target file (create file if needed)
3. Update original entry: Change `**Status**: pending` → `**Status**: promoted` and add `**Promoted**: <target file>`

## Recurring Pattern Detection

If logging something similar to an existing entry:

- Search first: `grep -r "keyword" .learnings/`
- Link entries: Add `**See Also**: ERR-20250110-001` in Metadata
- Bump priority if issue keeps recurring
- Consider systemic fix: Recurring issues often indicate missing documentation (→ promote to `CLAUDE.md`) or missing automation (→ add to `AGENTS.md`)

## Detection Triggers

Automatically log when you notice:

**Corrections** (→ learning with `correction` category):
- "No, that's not right..."
- "Actually, it should be..."
- "That's outdated..."

**Feature Requests** (→ feature request):
- "Can you also..."
- "I wish you could..."
- "Is there a way to..."

**Knowledge Gaps** (→ learning with `knowledge_gap` category):
- User provides information you didn't know
- Documentation you referenced is outdated
- API behavior differs from your understanding

**Errors** (→ error entry):
- Command returns non-zero exit code
- Exception or stack trace
- Unexpected output or behavior
- Timeout or connection failure

## Priority Guidelines

| Priority | When |
|---|---|
| critical | Blocks core functionality, data loss risk, security issue |
| high | Significant impact, affects common workflows, recurring issue |
| medium | Moderate impact, workaround exists |
| low | Minor inconvenience, edge case, nice-to-have |

## Area Tags

| Tag | Use for |
|---|---|
| frontend | UI, components, client-side code |
| backend | API, services, server-side code |
| infra | CI/CD, deployment, Docker, cloud |
| tests | Test files, testing utilities, coverage |
| docs | Documentation, comments, READMEs |
| config | Configuration files, environment, settings |

## Best Practices

- Log immediately — context is freshest right after the issue
- Be specific — future agents need to understand quickly
- Include reproduction steps — especially for errors
- Link related files — makes fixes easier
- Suggest concrete fixes — not just "investigate"
- Use consistent categories — enables filtering
- Promote aggressively — if in doubt, add to `CLAUDE.md` or `.github/copilot-instructions.md`
- Review regularly — stale learnings lose value

## Gitignore Options

Keep learnings local (per-developer):
```
.learnings/
```

Track learnings in repo (team-wide): Don't add to `.gitignore` — learnings become shared knowledge.

Hybrid (track templates, ignore entries):
```
.learnings/*.md
!.learnings/.gitkeep
```

## Multi-Agent Support (GitHub Copilot)

For GitHub Copilot, there is no hook support. Activation is manual:

Add to `.github/copilot-instructions.md`:

```
## Self-Improvement

After solving non-obvious issues, consider logging to `.learnings/`:
1. Use format from self-improvement skill
2. Link related entries with See Also
3. Promote high-value learnings to skills

Ask in chat: "Should I log this as a learning?"
```

Wersje

RepozytoriumWynikLicencja
Ta strona · mick-gsk/drift100MIT
openminis/minisskills100MIT
alirezarezvani/claude-skills100MIT
jdrhyne/agent-skills100MIT
1mancompany/onemancompany100Apache-2.0
1mancompany/onemancompany100Apache-2.0
bestagentkits/agency-skills100MIT
farm-fe/farm100MIT
borghei/Claude-Skills90MIT

Migawka bazy z 28.10.2026 · wersja paczki 8fc9a8fd2844 (skrót SHA-256 całej paczki)

Zgłoś problem z tym skillem: szkodliwa treść, błędny opis albo prośba autora o usunięcie.

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Uwagi i zgłoszenia

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