Borrowing it
Nothing to install: this file belongs to cpuguy96/StepCOVNet. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cpuguy96/StepCOVNet/master/.cursor/skills/agent-self-improvement/SKILL.mdgit clone --depth 1 https://github.com/cpuguy96/StepCOVNetWrote 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/cpuguy96/stepcovnet/agent-self-improvement)<a href="https://agentmods.dev/skills/cpuguy96/stepcovnet/agent-self-improvement"><img src="https://agentmods.dev/badge/skills/cpuguy96/stepcovnet/agent-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/skills/cpuguy96/stepcovnet/agent-self-improvement"><img src="https://agentmods.dev/badge/skills/cpuguy96/stepcovnet/agent-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 | $0.00036 | $0.00359 |
| Opus 5 | $0.00018 | $0.00179 |
| Sonnet 5 | $0.00007 | $0.00072 |
| Haiku 4.5 | $0.00004 | $0.00036 |
Grade A, and why
agent-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 9d 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.
What it actually says
Agent self-improvement
Steering corrections → promotion skill
On user steering, remember this, or a process mistake worth preserving:
- Open and follow steering-correction-promotion same turn.
- If brain files changed, run quick agent-brain-refresh.
Journal = receipt
| Step | Action |
|---|---|
| 1 | Artifact per promotion skill |
| 2 | Prepend JRN with Artifact path |
| 3 | Confirm artifact + journal id in chat |
Journal-only entries are incomplete (except explicit user deferral).
When to run
Immediately: steering correction, remember this, costly mistake, durable fix.
Periodically: after discrete tasks with process lessons; before switching task areas.
Session end: catch missed artifact + JRN pairs; run agent-brain-refresh if brain files changed.
JRN format
See steering-correction-promotion § JRN receipt and self-journal.md.
Do not
- Store research findings in the journal (use EXPERIMENT_LOG / DISCUSSION_NOTES)
- Create skills in
~/.cursor/skills-cursor/(Cursor internal)
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.
- 9d ago First seen · 42 lines · 36 tokens per session scan A 672e95096e32
agent-self-improvement is a skill published in the GitHub repository cpuguy96/StepCOVNet (22 stars, last pushed 15d ago), licensed Apache-2.0. It adds 36 tokens to every session and 359 once invoked, about $0.0002 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 2026-08-30.
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