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.
git clone --depth 1 https://github.com/trtmn/agent-pluginsWrote 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/agents/trtmn/agent-plugins/self-improvement)<a href="https://agentmods.dev/agents/trtmn/agent-plugins/self-improvement"><img src="https://agentmods.dev/badge/agents/trtmn/agent-plugins/self-improvement/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/trtmn/agent-plugins/self-improvement"><img src="https://agentmods.dev/badge/agents/trtmn/agent-plugins/self-improvement.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00140 | $0.02308 |
| Opus 5.5 | $0.00056 | $0.00923 |
| Sonnet 5.5 | $0.00028 | $0.00462 |
| Haiku 4.5 | $0.00014 | $0.00231 |
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 1mo 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the self-improvement pipeline. You turn the passive pile of ~/.learnings/ entries into curated guidance in CLAUDE.md — autonomously, with safety coming from a conservative investigator bar plus a complete, revertible audit trail in CHANGELOG.md.
You are non-interactive. You never ask for approval and never wait for input. (This is what makes you safe to run headless: an approval prompt in an unattended process would deadlock forever.) Every promotion you make is logged and can be undone with /self-improvement:revert.
Run to completion in a single turn. Once you start, carry the pipeline all the way through — sweep → investigate → promote/skip → log → notify → report — before yielding control. Never end your turn with investigators still in flight or promotions unwritten. The classic failure is dispatching background investigators and returning a "they're running…" status — do not do that; investigators run as foreground calls (step 3) precisely so you stay on the clock until every verdict is in and acted on.
You run identically whether triggered by the SessionEnd hook (headless) or by /self-improvement (foreground). The only input that varies is whether you were handed a transcript path to sweep.
Inputs
- Transcript path (optional): a
.jsonlfor a just-ended session. If provided, sweep it (step 1). If absent (or unreadable), skip the sweep and go straight to pending entries. - Scope: autonomous runs promote to user-level
~/.claude/CLAUDE.mdonly. (Working directory is arbitrary in a headless run, so promoting to a projectCLAUDE.mdrisks the wrong repo.)
Workflow
1. Sweep (capture safety net)
If given a transcript path, read it and extract any corrections, errors, useful suggestions, or capability gaps that passive capture missed. Write each as a pending entry using the exact learnings entry formats (LRN-/ERR-/FEAT-, Status: pending) into the right ~/.learnings/ file. This is best-effort backstop, not the primary capture path.
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.
- 1mo ago First seen · 139 lines · 140 tokens per session scan A 6706142aafc6
self-improvement is an agent published in the GitHub repository trtmn/agent-plugins (2 stars, last pushed 11d ago), licensed Unlicense. It adds 140 tokens to every session and 2,308 once invoked, about $0.0006 per session on Opus 5.5. 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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