Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/craftos-dev/craftbot/self-improving-agentnpx skills add CraftOS-dev/CraftBot --skill self-improving-agentgit clone --depth 1 https://github.com/CraftOS-dev/CraftBotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/craftos-dev/craftbot/self-improving-agent)<a href="https://agentmods.dev/skills/craftos-dev/craftbot/self-improving-agent"><img src="https://agentmods.dev/badge/skills/craftos-dev/craftbot/self-improving-agent.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00104 | $0.04840 |
| Opus 5 | $0.00052 | $0.02420 |
| Sonnet 5 | $0.00021 | $0.00968 |
| Haiku 4.5 | $0.00010 | $0.00484 |
Grade A, and why
self-improvement scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
98% identical to self-improvement — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 648 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
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 |
| Workflow improvements | Promote to AGENTS.md (OpenClaw workspace) |
| Tool gotchas | Promote to TOOLS.md (OpenClaw workspace) |
| Behavioral patterns | Promote to SOUL.md (OpenClaw workspace) |
OpenClaw Setup (Recommended)
OpenClaw is the primary platform for this skill. It uses workspace-based prompt injection with automatic skill loading.
Installation
Via ClawdHub (recommended):
clawdhub install self-improving-agent
Manual:
git clone https://github.com/peterskoett/self-improving-agent.git ~/.openclaw/skills/self-improving-agent
Remade for openclaw from original repo : https://github.com/pskoett/pskoett-ai-skills - https://github.com/pskoett/pskoett-ai-skills/tree/main/skills/self-improvement
Workspace Structure
OpenClaw injects these files into every session:
~/.openclaw/workspace/
├── AGENTS.md # Multi-agent workflows, delegation patterns
├── SOUL.md # Behavioral guidelines, personality, principles
├── TOOLS.md # Tool capabilities, integration gotchas
├── MEMORY.md # Long-term memory (main session only)
├── memory/ # Daily memory files
│ └── YYYY-MM-DD.md
└── .learnings/ # This skill's log files
├── LEARNINGS.md
├── ERRORS.md
└── FEATURE_REQUESTS.md
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _meta.json 140 B
- .clawhub/origin.json 153 B
- .learnings/ERRORS.md 75 B
- .learnings/FEATURE_REQUESTS.md 84 B
- .learnings/LEARNINGS.md 99 B
- assets/LEARNINGS.md 1.1 KB
- assets/SKILL-TEMPLATE.md 3.3 KB
- hooks/openclaw/handler.js 1.6 KB runs code
- hooks/openclaw/handler.ts 1.8 KB runs code
- hooks/openclaw/HOOK.md 589 B
- references/examples.md 8.1 KB
- references/hooks-setup.md 4.8 KB
- references/openclaw-integration.md 5.5 KB
- scripts/activator.sh 682 B runs code
- scripts/error-detector.sh 1.3 KB runs code
- scripts/extract-skill.sh 5.2 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 648 lines · 104 tokens per session scan A 651c4abaa265
self-improvement is a skill published in the GitHub repository CraftOS-dev/CraftBot (378 stars, last pushed 3d ago), licensed MIT. It adds 104 tokens to every session and 4,840 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to self-improvement, differing in 2 lines, and is treated as a copy.
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