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self-improving-agent

Automatically capture corrections, failures, and reusable discoveries into `.learnings/` files using signal-based filtering. Triggers when the user corrects the agent, a tool/command fails in a reusable way, or a better approach is discovered. Also handles periodic retention scoring and promotion of proven patterns into SOUL.md, AGENTS.md, or TOOLS.md.

作者: admin | 来源: ClawHub
源自
ClawHub
版本
V 1.0.0-alpha
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0
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概述
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版本历史

self-improving-agent

# Self-Improving Agent Capture what matters. Ignore noise. Promote proven patterns. Automate all of it. ## Source of truth - `.learnings/LEARNINGS.md` — corrections, env configs, reusable fixes, architecture decisions - `.learnings/ERRORS.md` — tool/command failures with fixes - `.learnings/FEATURE_REQUESTS.md` — missing capabilities worth tracking - `.learnings/ARCHIVE.md` — entries scored out during retention sweeps (never injected into context, but searchable) ## Write gate Before logging anything, the candidate must pass at least ONE filter: | Filter | Weight | Description | |---|---|---| | **Correction** | ALWAYS | Omar explicitly corrected the agent | | **Recurrence** | HIGH | Same issue hit 2+ times (check existing entries) | | **Cost-to-rediscover** | HIGH | Would take >2 tool calls to figure out again | | **Blast radius** | MEDIUM | Affects multiple skills, projects, or workflows | | **Decay risk** | MEDIUM | Non-obvious env/config detail that changes rarely | If NONE match → do not log. This replaces any arbitrary line-count threshold. Never log: - routine successes - facts obvious from docs or code - one-off tasks with no recurrence potential - anything already in MEMORY.md, SOUL.md, USER.md, or AGENTS.md ## Entry format LEARNINGS.md: ```markdown - [YYYY-MM-DD] [Category]: [Actionable takeaway] ``` Categories: `Correction`, `Env`, `Workflow`, `Testing`, `Skills`, `Git`, `Architecture` ERRORS.md: ```markdown - [YYYY-MM-DD] [Tool]: [What failed] → [Fix] ``` Mark fixed items with `[fixed]`. Delete stale entries during retention sweeps. ## Retention gate Instead of a hard line cap, score each entry periodically: | Signal | Score | |---|---| | Referenced or applied in last 30 days | +3 | | Matches active project context | +2 | | Direct correction from Omar | +2 | | Has prevented a repeat error | +3 | | Env/config still valid | +1 | | Superseded by newer entry | −5 | | >90 days old, never referenced | −3 | Action: - score ≥ 2 → keep - 0 ≤ score < 2 → archive to `.learnings/ARCHIVE.md` - score < 0 → delete Run this sweep during heartbeat maintenance (every ~3 days) or when LEARNINGS.md feels noisy. ## Automated triggers These fire without user prompting: 1. **Post-task scan**: After multi-step tasks, check for retried commands, error→workaround sequences, or avoidable file reads. If found, evaluate against write gate and log if it passes. 2. **Session-start sweep**: On `.learnings/LEARNINGS.md` read, flag entries >90 days old for retention scoring. 3. **Promotion detector**: After logging, scan for entries with the same `[Category]` tag appearing 3+ times. If found, auto-suggest a one-liner promotion to: - behavior/style → `SOUL.md` - workflow/process → `AGENTS.md` - tool/env gotcha → `TOOLS.md` 4. **Cross-session pattern detection**: When `memory_search` returns a daily note describing a workaround, check if `.learnings/` already has it. If not and it passes the write gate, log it. ## Dedup Before logging, scan existing entries for near-duplicates. If the lesson already exists, only update it if the new version is sharper or more general. ## Quality bar Every entry must help a future session avoid wasted work in under one glance.

标签

skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 auto-improving-agent-1776363962 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 auto-improving-agent-1776363962 技能

通过命令行安装

skillhub install auto-improving-agent-1776363962

下载 Zip 包

⬇ 下载 self-improving-agent v1.0.0-alpha

文件大小: 7.9 KB | 发布时间: 2026-4-17 14:09

v1.0.0-alpha 最新 2026-4-17 14:09
Initial release of self-improving-agent — automates capturing actionable corrections, errors, and discoveries to `.learnings/` files.

- Logs only high-value learnings, errors, and requests using a targeted signal-based filter.
- Periodically scores and prunes logged data to retain only proven, still-relevant entries.
- Promotes recurring or transferable lessons to higher-level skill, agent, or tool docs.
- Deduplicates and sharpens entries for high-impact, future-proof guidance.
- Automates all triggers to minimize user intervention and ensure continuous improvement.

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