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 PracticalSwan/agent-skills --skill false-positive-reviewergit clone --depth 1 https://github.com/PracticalSwan/agent-skillsWrote 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/practicalswan/agent-skills/false-positive-reviewer)<a href="https://agentmods.dev/skills/practicalswan/agent-skills/false-positive-reviewer"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/false-positive-reviewer/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/practicalswan/agent-skills/false-positive-reviewer"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/false-positive-reviewer.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 | $0.00049 | $0.01355 |
| Opus 5 | $0.00024 | $0.00678 |
| Sonnet 5 | $0.00010 | $0.00271 |
| Haiku 4.5 | $0.00005 | $0.00136 |
Grade A, and why
false-positive-reviewer 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
False-Positive Reviewer
Interpret AI-writing signals without turning them into an unsupported authorship verdict.
Authority
Use the evidence caveats and pattern guidance in ../avoid-ai-writing/SKILL.md. The original Skill explicitly treats flags as writing-quality signals, not proof of who or what wrote the text.
For cross-Skill work, follow ../avoid-ai-writing-router/references/handoff-contract.md and ../avoid-ai-writing-router/references/skill-graph.json.
Connection contract
Incoming
Accept interpretation work from:
avoid-ai-writing-routerviaROUTEwhen the user directly asks for an authorship or consequential interpretation.ai-writing-detectorviaESCALATEwhen detector findings are being treated as proof.- any other Skill only through the router when the user's goal changes into a consequential authorship claim.
Preserve the distinction between:
- deterministic detector evidence,
- model-only editorial observations,
- contextual facts supplied by the user,
- evidence not yet available.
Produce
Update the handoff envelope only with interpretation-relevant state:
- keep
consequential_authorship_claim: truewhen applicable, - identify what the existing evidence can and cannot establish,
- list additional evidence that would materially reduce uncertainty,
- set a router-return reason if the user requests fresh signal collection or changes intent.
Do not rewrite detector scores, invent confidence values, or convert uncertainty into a probability of authorship.
Terminal behavior
This Skill has no direct outgoing Skill edge.
If fresh signal collection is genuinely needed, return control to avoid-ai-writing-router with fresh_signal_collection_needed. The router may run ai-writing-detector and then route the updated evidence back for interpretation if the user's request still requires it.
If the user separately asks to rewrite or edit the text, return control to the router with the new intent. Do not jump directly into rewrite or mutation from this Skill.
What ships with it
2 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.
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 Changed cf14ed320acf
- 6d ago First seen · 130 lines · 49 tokens per session scan A 59544267c16e
false-positive-reviewer is a skill published in the GitHub repository PracticalSwan/agent-skills (14 stars, last pushed 5d ago), licensed MIT. It adds 49 tokens to every session and 1,355 once invoked, about $0.0002 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 2026-09-06.
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