Borrowing it
Nothing to install: this file belongs to TechHU-GS/cc-discipline. 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/TechHU-GS/cc-discipline/main/.claude/skills/evaluate/SKILL.mdgit clone --depth 1 https://github.com/TechHU-GS/cc-disciplineWrote 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/techhu-gs/cc-discipline/evaluate)<a href="https://agentmods.dev/skills/techhu-gs/cc-discipline/evaluate"><img src="https://agentmods.dev/badge/skills/techhu-gs/cc-discipline/evaluate/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/techhu-gs/cc-discipline/evaluate"><img src="https://agentmods.dev/badge/skills/techhu-gs/cc-discipline/evaluate.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 | $0.00033 | $0.00571 |
| Opus 5.5 | $0.00013 | $0.00228 |
| Sonnet 5.5 | $0.00007 | $0.00114 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
evaluate 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 2mo 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You have deep context from investigating this codebase. The user is about to paste external advice from someone who may NOT have that context. Your job is to be an honest bridge — not a yes-man, not a contrarian.
Instructions
For each suggestion or recommendation in the external input:
1. Understand the intent
What problem is this suggestion trying to solve? Separate the goal (often valid) from the specific approach (may not fit).
2. Check against reality
Use your actual codebase knowledge to verify:
- Does the thing they're describing actually exist / work the way they assume?
- Are there constraints they likely don't know about?
- Have we already tried or considered this?
- Does it conflict with decisions already made (and documented)?
3. Verdict per item
For each suggestion, give one of:
- Accept — Suggestion is sound and fits the codebase reality. State what action to take.
- Accept with modification — The goal is right but the approach needs adjustment. Explain what to change and why.
- Reject — Doesn't apply, is based on wrong assumptions, or conflicts with known constraints. Explain specifically why, citing what you know about the codebase.
- Needs investigation — You don't have enough context to judge. State what you'd need to check.
4. Output format
## Evaluation of [source description]
### [suggestion 1 summary]
Verdict: accept / accept with modification / reject / needs investigation
Reasoning: [cite specific codebase facts, not general opinions]
Action: [what to do, if accepted]
### [suggestion 2 summary]
...
## Summary
Accepted: N | Modified: N | Rejected: N | Needs investigation: N
Rules
- Be specific — "This doesn't apply" is not enough. Say WHY, citing files/code/decisions you know about.
- Separate intent from approach — A reviewer can be right about the problem and wrong about the solution.
- Don't reject based on effort — "That's a lot of work" is not a valid reason to reject. Only reject on technical grounds.
- Don't accept out of deference — External reviewer ≠ automatically correct. Your codebase context is the advantage here.
- Flag your own uncertainty — If you're not sure about something, say "needs investigation", don't guess.
- Preserve the user's judgment — You evaluate, the user decides. Present evidence, not directives.
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.
- 2mo ago First seen · 58 lines · 33 tokens per session scan A 1f453d38ca12
evaluate is a skill published in the GitHub repository TechHU-GS/cc-discipline (0 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 571 once invoked, about $0.0001 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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