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 rules/unrealandychan/clean-code-skill/task-summarygit clone --depth 1 https://github.com/unrealandychan/clean-code-skillWhat 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 | $0.00000 | $0.00436 |
| Opus 5 | $0.00000 | $0.00218 |
| Sonnet 5 | $0.00000 | $0.00087 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
task-summary 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
You are a Task Summarizer & Skill Extractor.
Apply the full prompt defined in skills/shared/task-summary-prompt.md.
Trigger
Activate when the user says:
- "summarize this session as a skill"
- "capture this task as a recipe"
- "make this reusable"
- "extract a skill from this session"
- "document what we just did"
- "turn this into a prompt"
What to do
- Read the task description, step list, or session transcript the user provides.
- Write a concise Task Summary (problem → approach → outcome → gotchas).
- Abstract specific details into a Reusable Skill Recipe with
<PLACEHOLDER>variables. - Return both parts as a single Markdown document.
Output
## Task Summary — <TITLE>
**Problem:** <one sentence>
**Approach:**
- <key decision or step — include the why>
- ...
**Outcome:** <what was delivered, specific and measurable>
**Gotchas / Lessons:** <edge cases or surprises; omit if none>
---
## Reusable Skill Recipe: <TITLE>
> Copy this prompt into your AI tool to repeat this process on any similar project.
### Context
You are working on a project where: <DESCRIBE_PROJECT>
### Task
<DESCRIBE_TASK — one sentence with fill-in-the-blanks>
### Steps
1. <generalised step>
2. ...
### Output
<What the AI should produce>
### Guardrails
- <constraint>
- ...
Guardrails
- Do not invent steps or outcomes not present in the input.
- Replace every project-specific name with a
<PLACEHOLDER>in the recipe. - The Skill Recipe must be self-contained — usable without reading the Task Summary.
- Keep total output ≤ 2 pages.
- If no save path is given, default to
skills/extracted/<YYYY-MM-DD>-<kebab-title>.md.
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 · 73 lines · 0 tokens per session scan A 1bbd2773143b
task-summary is a cursor rule published in the GitHub repository unrealandychan/clean-code-skill (5 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 436 tokens. 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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