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 CDCgov/cdc-open-viz --skill react-doctor-fixgit clone --depth 1 https://github.com/CDCgov/cdc-open-vizWrote 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/cdcgov/cdc-open-viz/react-doctor-fix)<a href="https://agentmods.dev/skills/cdcgov/cdc-open-viz/react-doctor-fix"><img src="https://agentmods.dev/badge/skills/cdcgov/cdc-open-viz/react-doctor-fix.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00069 | $0.00462 |
| Opus 5 | $0.00034 | $0.00231 |
| Sonnet 5 | $0.00014 | $0.00092 |
| Haiku 4.5 | $0.00007 | $0.00046 |
Grade A, and why
react-doctor-fix 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 8d 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
React Doctor Fix
Workflow
- Extract the target path from the user's message. If no path is provided, default to
packages/map. - Derive the review filename by replacing
/with-in the path (e.g.packages/map→_react-doctor/output/packages-map-review.md). - Read the review file. If it doesn't exist, tell the user to run the
react-doctorskill first. - List the available rule type sections found in the file and ask the user which one they want to work on:
Available rule types:
1. react/jsx-key (2 issues)
2. react-hooks/exhaustive-deps (2 issues)
3. react-hooks/rules-of-hooks (1 issue)
Which would you like to work on?
-
Once the user selects a section, work through each issue in that section one at a time: a. State the issue clearly — file path, line number, and what's wrong. b. Show the fix using
// Before/// Aftercomments. c. Apply the fix to the file. d. Mark the issue as done in the review file:- [x]e. Ask the user to confirm before moving to the next issue. -
When all issues in the section are resolved, ask if the user wants to move on to another rule type.
Constraints
- Only fix what is listed in the review file.
- Preserve existing code style, naming conventions, and imports.
- If a fix requires a new dependency, flag it with a
// NOTE:comment and do not apply it automatically. - If an issue is ambiguous or the fix could have side effects, explain the concern and ask before proceeding.
- Keep the review file up to date as issues are resolved.
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.
- 8d ago First seen · 40 lines · 69 tokens per session scan A 63816ad516dd
react-doctor-fix is a skill published in the GitHub repository CDCgov/cdc-open-viz (55 stars, last pushed 3d ago), licensed Apache-2.0. It adds 69 tokens to every session and 462 once invoked, about $0.0003 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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