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 commands/rasputinkaiser/self-improvement-plugin/patternsgit clone --depth 1 https://github.com/RasputinKaiser/Self-Improvement-PluginWhat 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 | $0.00019 | $0.00174 |
| Opus 5 | $0.00010 | $0.00087 |
| Sonnet 5 | $0.00004 | $0.00035 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade A, and why
patterns 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 yesterday.
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
Run python3 ${CLAUDE_PLUGIN_ROOT}/scripts/agent_patterns.py (full report, not
--brief) and present it to the user verbatim with light formatting.
Then add a one-line interpretation:
- If success rate < 70% → "success rate is low; consider
/improveto attack the top failure topic." - If an approach→outcome correlation shows a bucket with >=80% success and >=3
samples → "approach
<metric>=<bucket>correlates with success — lean into it." - If no outcomes recorded → "no outcomes yet; complete tasks with the Stop hook active to populate metrics."
Do not edit anything. This is a read-only dashboard.
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.
- yesterday First seen · 16 lines · 19 tokens per session scan A 889e127175d8
patterns is a command published in the GitHub repository RasputinKaiser/Self-Improvement-Plugin (6 stars, last pushed 4d ago), licensed MIT. It adds 19 tokens to every session and 174 once invoked, about $0.0001 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.
Other commands, from other repositories
feature
Orchestrate a complete feature through discovery, spec, implementation, and review.
test
Design or run focused test validation for a task, bug, or diff.
mvp-spec
Research and produce a strict MVP spec with small 1-2 hour tasks and explicit out of scope.
research
Research a technical or product question.
review-pr
Command "review-pr" from saski/arnesto, covering review pr, what this command does, workflow steps, phase 0: initialize review and phase 1: analysis & summary.
evolution-engine
Scan feedback and generate evolution proposals for rule/skill upgrades.