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Official agent skill

Fp Check

by trailofbits in trailofbits/skills

Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each.

OfficialCC-BY-SA-4.0Auto-check: notes

Install Fp Check

skills CLI
$ npx skills add trailofbits/skills --skill fp-check -a claude-code

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

GitHub CLI
$ gh skill install trailofbits/skills fp-check --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/trailofbits/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/fp-check/skills/fp-check .claude/skills/fp-check && 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
fp-check
GitHub stars
7.4k
Used in
2 other repos
Token cost
~1.7k tokens
SKILL.md length
795 words
Files
9 (incl. references, assets)
Skills in repo
79
Repo updated
First seen
Licence
CC-BY-SA-4.0

At a glance

Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each.

  • Works in 4 steps: Run Step 0 for all bugs first —… → Route each bug independently (some may… → Process all standard-routed bugs first,… → …
  • Asked whether a specific finding is real
  • SKILL.md covers When to Use, When NOT to Use, Rationalizations to Reject and Step 0: Understand the Claim…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Fp Check is an agent skill from trailofbits/skills, published by the product's own GitHub organization. Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each. Use when asked whether a specific finding is real, exploitable, or a false positive, or to verify or validate a suspected vulnerability — not for hunting or discovering new bugs.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files and assets (for example `agents/openai.yaml`, `references/bug-class-verification.md` and `references/deep-verification.md`).

The repository describes itself as: Trail of Bits Claude Code skills for security research, vulnerability detection, and audit workflows. The licence is CC-BY-SA-4.0.

When your agent uses it

  • Asked whether a specific finding is real
  • A false positive
  • Validate a suspected vulnerability — not for hunting
  • Discovering new bugs

Example prompts

  • “/fp-check”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob, LSP, Bash, Task, Write, Edit, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, TaskGet

Workflow steps

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

  1. Run Step 0 for all bugs first — restating each claim often collapses obvious false positives immediately
  2. Route each bug independently (some may be standard, others deep)
  3. Process all standard-routed bugs first, then deep-routed bugs
  4. After all bugs are verified, check for exploit chains — findings that individually failed gate review may combine to form a viable attack

What it can do on your machine

Read from SKILL.md and the folder at commit 82fe822. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • LSP
    • Bash
    • Task
    • Write
    • Edit
    • AskUserQuestion
    • TaskCreate

    …and 3 more on the same allowed-tools line.

    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

Fp Check loads about 1.7k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 88 tokens; SKILL.md has 795 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Grep, Glob, LSP, Bash, Task, Write, Edit, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, T

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 trailofbits/skills at commit 82fe822, republished under its CC-BY-SA-4.0 licence (© trailofbits). 795 words, ~1,681 tokens.

Download SKILL.mdSave it as .claude/skills/fp-check/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
fp-check
description
Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each. Use when asked whether a specific finding is real, exploitable, or a false positive, or to verify or validate a suspected vulnerability — not for hunting or discovering new bugs.
allowed-tools
Read, Grep, Glob, LSP, Bash, Task, Write, Edit, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, TaskGet

False Positive Check

When to Use

  • "Is this bug real?" or "is this a true positive?"
  • "Is this a false positive?" or "verify this finding"
  • "Check if this vulnerability is exploitable"
  • Any request to verify or validate a specific suspected bug

When NOT to Use

  • Finding or hunting for bugs ("find bugs", "security analysis", "audit code")
  • General code review for style, performance, or maintainability
  • Feature development, refactoring, or non-security tasks
  • When the user explicitly asks for a quick scan without verification

Rationalizations to Reject

If you catch yourself thinking any of these, STOP.

RationalizationWhy It's WrongRequired Action
"Rapid analysis of remaining bugs"Every bug gets full verificationReturn to task list, verify next bug through all phases
"This pattern looks dangerous, so it's a vulnerability"Pattern recognition is not analysisComplete data flow tracing before any conclusion
"Skipping full verification for efficiency"No partial analysis allowedExecute all steps per the chosen verification path
"The code looks unsafe, reporting without tracing data flow"Unsafe-looking code may have upstream validationTrace the complete path from source to sink
"Similar code was vulnerable elsewhere"Each context has different validation, callers, and protectionsVerify this specific instance independently
"This is clearly critical"LLMs are biased toward seeing bugs and overrating severityComplete devil's advocate review; prove it with evidence

Step 0: Understand the Claim and Context

Before any analysis, restate the bug in your own words. If you cannot do this clearly, ask the user for clarification. Half of false positives collapse at this step — the claim doesn't make coherent sense when restated precisely.

Document:

  • What is the exact vulnerability claim? (e.g., "heap buffer overflow in parse_header() when content_length exceeds 4096")
  • What is the alleged root cause? (e.g., "missing bounds check before memcpy at line 142")
  • What is the supposed trigger? (e.g., "attacker sends HTTP request with oversized Content-Length header")
  • What is the claimed impact? (e.g., "remote code execution via controlled heap corruption")
  • What is the threat model? What privilege level does this code run at? Is it sandboxed? What can the attacker already do before triggering this bug? (e.g., "unauthenticated remote attacker vs privileged local user"; "runs inside Chrome renderer sandbox" vs "runs as root with no sandbox")
  • What is the bug class? Classify the bug and consult bug-class-verification.md for class-specific verification requirements that supplement the generic phases below.
  • Execution context: When and how is this code path reached during normal execution?
  • Caller analysis: What functions call this code and what input constraints do they impose?
  • Architectural context: Is this part of a larger security system with multiple protection layers?
  • Historical context: Any recent changes, known issues, or previous security reviews of this code area?

Route: Standard vs Deep Verification

After Step 0, choose a verification path.

Show full SKILL.md (338 more words)Show less
Standard Verification

Use when ALL of these hold:

  • Clear, specific vulnerability claim (not vague or ambiguous)
  • Single component — no cross-component interaction in the bug path
  • Well-understood bug class (buffer overflow, SQL injection, XSS, integer overflow, etc.)
  • No concurrency or async involved in the trigger
  • Straightforward data flow from source to sink

Follow standard-verification.md. No task tracking — work through the linear checklist sequentially, documenting findings inline.

Deep Verification

Use when ANY of these hold:

  • Ambiguous claim that could be interpreted multiple ways
  • Cross-component bug path (data flows through 3+ modules or services)
  • Race conditions, TOCTOU, or concurrency in the trigger mechanism
  • Logic bugs without a clear spec to verify against
  • Standard verification was inconclusive or escalated
  • User explicitly requests full verification

Follow deep-verification.md. Track each phase as a task with explicit dependencies, and execute the phases using the plugin's analysis agents.

Default

Start with standard. Standard verification has two built-in escalation checkpoints that route to deep when complexity exceeds the linear checklist.

Batch Triage

When verifying multiple bugs at once:

  1. Run Step 0 for all bugs first — restating each claim often collapses obvious false positives immediately
  2. Route each bug independently (some may be standard, others deep)
  3. Process all standard-routed bugs first, then deep-routed bugs
  4. After all bugs are verified, check for exploit chains — findings that individually failed gate review may combine to form a viable attack

Final Summary

After processing ALL suspected bugs, provide:

  1. Counts: X TRUE POSITIVES, Y FALSE POSITIVES
  2. TRUE POSITIVE list: Each with brief vulnerability description
  3. FALSE POSITIVE list: Each with brief reason for rejection

References

  • Standard Verification — Linear single-pass checklist for straightforward bugs
  • Deep Verification — Full task-based orchestration for complex bugs
  • Gate Reviews — Six mandatory gates and verdict format
  • Bug-Class Verification — Class-specific verification requirements for memory corruption, logic bugs, race conditions, integer issues, crypto, injection, info disclosure, DoS, and deserialization
  • False Positive Patterns — 13-item checklist and red flags for common false positive patterns
  • Evidence Templates — Documentation templates for data flow, mathematical proofs, attacker control, and devil's advocate reviews

© trailofbits, CC-BY-SA-4.0. 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 8 other files (references, assets) in plugins/fp-check/skills/fp-check of trailofbits/skills.

  • SKILL.md
  • agents/openai.yaml
  • assets/trail-of-bits-mark.svg
  • references/bug-class-verification.md
  • references/deep-verification.md
  • references/evidence-templates.md
  • references/false-positive-patterns.md
  • references/gate-reviews.md
  • references/standard-verification.md

Open the folder on GitHubat commit 82fe822

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in trailofbits/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Fp Check 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.

Fp Check compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Fp Check this skilltrailofbits/skills7.4k2 repos~1.7kAutomated safety check: NotesCC-BY-SA-4.0
Performing False Positive Reduction In Siemmukul975/Anthropic-Cybersecurity-Skills34k—~1.9kAutomated safety check: PassApache-2.0
False Positive Reviewerconorbronsdon/avoid-ai-writing4.9k—~1.1kAutomated safety check: PassMIT
Verifyasgeirtj/system_prompts_leaks69k—~3kAutomated safety check: PassCC0-1.0
Verify Thiscursor/plugins10k2 repos~693Automated safety check: PassNone
Bug Huntersickn33/agentic-awesome-skills47k2 repos~2kAutomated safety check: PassMIT

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Questions about Fp Check

What does Fp Check do?

Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each. Fp Check is an agent skill from trailofbits/skills, published by the product's own GitHub organization. Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each.

When should I use Fp Check?

Fp Check fits situations like: asked whether a specific finding is real; A false positive; validate a suspected vulnerability — not for hunting; discovering new bugs.

How do I install Fp Check in Claude Code?

Run `npx skills add trailofbits/skills --skill fp-check -a claude-code`. Or copy the skill folder (plugins/fp-check/skills/fp-check in trailofbits/skills) into .claude/skills/fp-check in your project. Claude Code loads it when a task matches its description.

How do I install Fp Check in Codex?

Run `npx skills add trailofbits/skills --skill fp-check -a codex`. Or copy the skill folder (plugins/fp-check/skills/fp-check in trailofbits/skills) into .agents/skills/fp-check in your project. Codex loads it when a task matches its description.

Can I use Fp Check 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 trailofbits/skills --skill fp-check -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fp-check, .gemini/skills/fp-check, .github/skills/fp-check and .opencode/skills/fp-check in your project.

What does Fp Check need to run?

SKILL.md names no scripts, command-line tools or credentials: Fp Check is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob, LSP, Bash, Task, Write, Edit, AskUserQuestion, TaskCreate, TaskUpdate, TaskList, TaskGet.

Does Fp Check 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 Fp Check safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Fp Check use?

Fp Check is published under the CC-BY-SA-4.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fp Check use?

About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.3k tokens, read only when the agent opens those files.

What are the alternatives to Fp Check?

Skills that share tags, products or a category with Fp Check: Performing False Positive Reduction In Siem (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), False Positive Reviewer (conorbronsdon/avoid-ai-writing, 4.9k stars), Verify (asgeirtj/system_prompts_leaks, 69k stars) and Verify This (cursor/plugins, 10k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fp Check?

trailofbits (a GitHub organization, an official publisher) maintains it in trailofbits/skills, which has 7,400 GitHub stars. The repository holds 79 skills in this directory. The repository was last updated on October 2, 2026.

Source: trailofbits/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.