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 skills add vvedantb/eva --skill skill-doctorgit clone --depth 1 https://github.com/vvedantb/evaWrote 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/vvedantb/eva/skill-doctor)<a href="https://agentmods.dev/skills/vvedantb/eva/skill-doctor"><img src="https://agentmods.dev/badge/skills/vvedantb/eva/skill-doctor/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/vvedantb/eva/skill-doctor"><img src="https://agentmods.dev/badge/skills/vvedantb/eva/skill-doctor.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 | $0.00059 | $0.02361 |
| Opus 5.5 | $0.00024 | $0.00944 |
| Sonnet 5.5 | $0.00012 | $0.00472 |
| Haiku 4.5 | $0.00006 | $0.00236 |
Grade A, and why
skill-doctor 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 4d 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.
This is a copy
86% identical to skill-doctor — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
skill-doctor
Grade the user's agent setup by scoring recent local agent conversations, then propose concrete skill edits and render one shareable report page.
The report can cover conversations in the current repository, conversations in selected projects, or all local conversations. It can evaluate project skills alone or project and global skills together.
Everything runs locally. Never upload transcripts, session files, or any excerpt of them anywhere. The only shareable artifact is the report the user chooses to post.
Let SKILL_ROOT be the directory containing this SKILL.md.
Step 0: Start the run
Verify the executing harness
Read $SKILL_ROOT/references/supported-harnesses.md and identify the harness executing this skill from the runtime context. If it is unsupported or cannot be identified confidently, follow the reference's stop behavior. Do not create a report directory or read conversation history.
Ask which conversations to grade
First check whether the current directory is inside a git repository:
git rev-parse --show-toplevel
Use the harness's user-question tool when available.
When a current repository is available, ask “Which conversations should I grade?” with:
- Conversations in this repository — recommended.
- All conversations.
- Choose projects to analyze.
When there is no current repository, ask the same question with:
- All conversations — recommended.
- Choose projects to analyze.
If the user chooses projects, ask for one or more project paths. Expand and validate every path as a git repository before continuing. The run produces one combined report across those projects.
Ask which skills to evaluate
Then ask “Which skills should I evaluate?” with:
- Project skills + global skills — recommended.
- Project skills only.
For an all-conversations run, “Project skills” means skills from local git repositories inferred from the conversations' working directories. After these answers, proceed immediately.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/pierre-diffs.js 1130 KB runs code
- assets/warp-pixel-icon.svg 4.3 KB
- references/skill-improvements.md 1.9 KB
- references/supported-harnesses.md 2.6 KB
- scorers/code-quality.md 4.7 KB
- scorers/efficiency.md 3.3 KB
- scorers/procedure-compliance.md 3.3 KB
- scorers/verbosity.md 3.1 KB
- scripts/__pycache__/warp_decoder.cpython-314.pyc 15 KB
- scripts/collect_sessions.py 71 KB runs code
- scripts/render_report.py 26 KB runs code
- scripts/warp_decoder.py 11 KB runs code
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.
- 4d ago First seen · 185 lines · 59 tokens per session scan A 9ded60ae72b5
skill-doctor is a skill published in the GitHub repository vvedantb/eva (101 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 2,361 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to skill-doctor, differing in 0 lines, and is treated as a copy.
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