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 skills add ashermahonin/agentic-skills --skill self-improvement-loopgit clone --depth 1 https://github.com/ashermahonin/agentic-skillsWrote 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/ashermahonin/agentic-skills/self-improvement-loop)<a href="https://agentmods.dev/skills/ashermahonin/agentic-skills/self-improvement-loop"><img src="https://agentmods.dev/badge/skills/ashermahonin/agentic-skills/self-improvement-loop.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 | $0.00072 | $0.00716 |
| Opus 5 | $0.00036 | $0.00358 |
| Sonnet 5 | $0.00014 | $0.00143 |
| Haiku 4.5 | $0.00007 | $0.00072 |
Grade A, and why
self-improvement-loop 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-improvement loop
Purpose
Correct a specific weakness in the system around the model. This event loop changes prompts, skills, routing, tools, memory, or evaluations; it does not train model weights.
Failure evidence
- Read
references/improvement-loop.md. - Save the resume point in the original task.
- Record the triggering event, expected behavior, available logs or checks, and smallest reproduction.
- Classify the failure: route, context, documentation, tool contract, prompt, memory, evaluation, permission, handoff, or implementation.
- Decide whether the fault belongs to the product or the agent system. Route ordinary code defects to implementation.
- Define one measurable improvement target and a stop condition.
Repair cycle
- Reproduce the failure and identify the first wrong decision supported by evidence.
- Compare the smallest plausible repairs when the cause is uncertain. Verify current external behavior before changing a technical contract.
- Change the narrowest durable surface: trigger description, route, procedure, reference, tool schema, context policy, memory rule, or evaluator.
- Re-run the reproduction and one nearby non-regression case.
- Add a behavioral regression check when it can catch the same failure class without matching preferred wording.
- Write a short project-memory note only when the lesson is likely to help a future task. Use the active equivalent of
53-agent-learning-log.md. - Resume the original task from the saved point.
Event loop rules
- Run one observe, analyze, repair, validate, remember, resume cycle for a failure class.
- A new cycle needs new evidence, not a feeling that the previous repair was incomplete.
- Keep the user's task moving; process improvement is not the primary deliverable.
- Stop after two ineffective repairs for the same class and report the unresolved cause.
- Never increase autonomy, permissions, retention, external access, or unattended execution as an implicit repair.
What ships with it
2 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.
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.
- 7d ago First seen · 71 lines · 72 tokens per session scan A 057d9bfbe581
self-improvement-loop is a skill published in the GitHub repository ashermahonin/agentic-skills (10 stars, last pushed 14d ago), licensed MIT. It adds 72 tokens to every session and 716 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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