Agent skill

False Positive Reviewer

by conorbronsdon in conorbronsdon/avoid-ai-writing

A skill your agent uses when a user asks what AI-writing flags mean, whether detector output proves AI authorship, or wants a careful interpretation of possible false positives, especially for…

MITAuto-check passedWriting & Content

Install False Positive Reviewer

skills CLI
$ npx skills add conorbronsdon/avoid-ai-writing --skill false-positive-reviewer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install conorbronsdon/avoid-ai-writing false-positive-reviewer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/conorbronsdon/avoid-ai-writing.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/false-positive-reviewer .claude/skills/false-positive-reviewer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
false-positive-reviewer
GitHub stars
4.9k
Token cost
~1.1k tokens
SKILL.md length
523 words
Files
2
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when a user asks what AI-writing flags mean, whether detector output proves AI authorship, or wants a careful interpretation of possible false positives, especially for…

  • Works in 6 steps: Identify which observations are… → Explain the strongest signals and… → Consider genre, second-language writing,… → …
  • A user asks what AI-writing flags mean
  • SKILL.md covers Authority, Connection contract, AI-engineering evidence lens and Workflow, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

False Positive Reviewer is an agent skill from conorbronsdon/avoid-ai-writing. Use when a user asks what AI-writing flags mean, whether detector output proves AI authorship, or wants a careful interpretation of possible false positives, especially for academic, hiring, publication, disciplinary, or other consequential decisions.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Writing & Content, covering Humanizing AI text. The repository describes itself as: Skill that audits and rewrites content to remove AI writing patterns. Use it with your favorite agents including Claude Code, OpenClaw, Codex, and Hermes. The licence is MIT.

When your agent uses it

  • A user asks what AI-writing flags mean
  • Whether detector output proves AI authorship
  • Wants a careful interpretation of possible false positives
  • Especially for academic

Example prompts

  • “/false-positive-reviewer”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Identify which observations are deterministic detector hits, model-only editorial observations, or contextual facts supplied by the user.
  2. Explain the strongest signals and plausible human reasons they can appear.
  3. Consider genre, second-language writing, technical register, deadline pressure, editing tools, typography software, and the writer's known…
  4. If an adequate audit is missing and the user wants one, return control to the router with a fresh-signal request. Do not call the detector…
  5. For consequential decisions, do not turn a score or pattern list into a definitive claim of AI use, cheating, fraud, dishonesty, or…
  6. Suggest evidence that is more probative for the legitimate decision, such as source history, drafts, revision logs, direct discussion with…

What it can do on your machine

Read from SKILL.md and the folder at commit 5a5cf6a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

False Positive Reviewer loads about 1.1k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 523 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from conorbronsdon/avoid-ai-writing at commit 5a5cf6a, republished under its MIT licence (© conorbronsdon). 523 words, ~1,091 tokens.

Download SKILL.mdSave it as .claude/skills/false-positive-reviewer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
false-positive-reviewer
description
Use when a user asks what AI-writing flags mean, whether detector output proves AI authorship, or wants a careful interpretation of possible false positives, especially for academic, hiring, publication, disciplinary, or other consequential decisions.
version
3.37.0
license
MIT

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-router via ROUTE when the user directly asks for an authorship or consequential interpretation.
  • ai-writing-detector via ESCALATE when 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: true when 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.

This keeps interpretation terminal in the Skill graph and prevents reviewer-detector cycles.

AI-engineering evidence lens

Apply the agency-ai-engineer lens encoded in ../avoid-ai-writing-router/references/agency-role-lenses.md:

  • treat detector output as noisy evidence rather than ground truth,
  • account for context mode, genre, second-language writing, technical register, editing software, and baseline writing style,
  • separate model behavior from human attribution,
  • avoid false precision,
  • prefer process evidence when the decision has consequences.
Show full SKILL.md (206 more words)Show less

Workflow

  1. Identify which observations are deterministic detector hits, model-only editorial observations, or contextual facts supplied by the user.
  2. Explain the strongest signals and plausible human reasons they can appear.
  3. Consider genre, second-language writing, technical register, deadline pressure, editing tools, typography software, and the writer's known baseline when those facts are available.
  4. If an adequate audit is missing and the user wants one, return control to the router with a fresh-signal request. Do not call the detector directly.
  5. For consequential decisions, do not turn a score or pattern list into a definitive claim of AI use, cheating, fraud, dishonesty, or suitability.
  6. Suggest evidence that is more probative for the legitimate decision, such as source history, drafts, revision logs, direct discussion with the writer, or task-specific process evidence.

Stop conditions

Stop when the interpretation question is answered. If more signal collection or a different action is requested, return control to the router rather than opening a direct Skill loop.

Output

Distinguish what the text actually shows, what it may suggest, what it cannot establish, which evidence came from executed tooling versus model-only review, what additional evidence would reduce uncertainty, and whether control should return to the router for a newly requested stage.

© conorbronsdon, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/false-positive-reviewer of conorbronsdon/avoid-ai-writing.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 5a5cf6a

Compare with similar skills

False Positive Reviewer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

False Positive Reviewer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
False Positive Reviewer this skillconorbronsdon/avoid-ai-writing4.9k—~1.1kAutomated safety check: PassMIT
HumanizerAzure-Samples/interview-coach-agent-framework17338 repos~5.8kAutomated safety check: PassMIT
User-Facing Text Cleanupguillaumemeyer/watermarks-remover24k—~3.5kAutomated safety check: PassMIT
Install Anti Sloptrycompai/crm11k1 repos~881Automated safety check: PassMIT
Stop SlopXe/site7328 repos~423Automated safety check: PassMIT
Chinese Text Humanizerop7418/Humanizer-zh19k—~2kAutomated safety check: PassMIT

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Questions about False Positive Reviewer

What does False Positive Reviewer do?

A skill your agent uses when a user asks what AI-writing flags mean, whether detector output proves AI authorship, or wants a careful interpretation of possible false positives, especially for…. False Positive Reviewer is an agent skill from conorbronsdon/avoid-ai-writing. Use when a user asks what AI-writing flags mean, whether detector output proves AI authorship, or wants a careful interpretation of possible false positives, especially for academic, hiring, publication, disciplinary, or other consequential decisions.

When should I use False Positive Reviewer?

False Positive Reviewer fits situations like: A user asks what AI-writing flags mean; whether detector output proves AI authorship; wants a careful interpretation of possible false positives; especially for academic.

How do I install False Positive Reviewer in Claude Code?

Run `npx skills add conorbronsdon/avoid-ai-writing --skill false-positive-reviewer -a claude-code`. Or copy the skill folder (skills/false-positive-reviewer in conorbronsdon/avoid-ai-writing) into .claude/skills/false-positive-reviewer in your project. Claude Code loads it when a task matches its description.

How do I install False Positive Reviewer in Codex?

Run `npx skills add conorbronsdon/avoid-ai-writing --skill false-positive-reviewer -a codex`. Or copy the skill folder (skills/false-positive-reviewer in conorbronsdon/avoid-ai-writing) into .agents/skills/false-positive-reviewer in your project. Codex loads it when a task matches its description.

Can I use False Positive Reviewer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add conorbronsdon/avoid-ai-writing --skill false-positive-reviewer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/false-positive-reviewer, .gemini/skills/false-positive-reviewer, .github/skills/false-positive-reviewer and .opencode/skills/false-positive-reviewer in your project.

What does False Positive Reviewer need to run?

SKILL.md names no scripts, command-line tools or credentials: False Positive Reviewer is instructions for the agent only.

Does False Positive Reviewer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is False Positive Reviewer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does False Positive Reviewer use?

False Positive Reviewer is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does False Positive Reviewer use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to False Positive Reviewer?

Skills that share tags, products or a category with False Positive Reviewer: Humanizer (Azure-Samples/interview-coach-agent-framework, 173 stars), User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 24k stars), Install Anti Slop (trycompai/crm, 11k stars) and Stop Slop (Xe/site, 732 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains False Positive Reviewer?

conorbronsdon (a GitHub user) maintains it in conorbronsdon/avoid-ai-writing, which has 4,938 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 8, 2026.

Source: conorbronsdon/avoid-ai-writing on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.