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Trailmark Review Gate

OrganizationPopular
trailofbits
trailmark-review-gate

Runs a Trailmark structural review gate over a branch, pull request, fix commit, release diff, or git ref range to detect new entrypoints, new tainted paths, removed validation or authorization calls, privilege-boundary drift, blast-radius growth, complexity growth, and newly reachable sensitive sinks. Use when reviewing a PR, branch, remediation commit, or release diff where graph-level security regressions should be checked before merge.

Overview

Publishertrailofbits
Repositoryskills
Skill nametrailmark-review-gate
Stars
7.3K
Forks
624
Bundled files
5
LicenseCC-BY-SA-4.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by trailofbits on GitHub. Read the source before you install it.

Installation

Install the Trailmark Review Gate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/trailofbits/skills/tree/main/plugins/trailmark/skills/trailmark-review-gate
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/trailofbits/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/trailmark/skills/trailmark-review-gate .claude/skills/trailmark-review-gate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trailmark Review Gate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trailmark Review Gate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trailmark Review Gate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Trailmark Review Gate

Apply deterministic security gate rules to Trailmark structural diff evidence. This skill does not replace line-level review. It produces a compact structural packet reviewers can cite while they inspect the code.

When to Use

  • Reviewing a branch, pull request, release diff, or fix commit
  • Checking whether a change expands attack surface
  • Looking for removed validation or authorization on reachable paths
  • Comparing before/after taint, privilege-boundary, blast-radius, or complexity signals
  • Producing graph evidence for a differential review

When NOT to Use

  • Single-snapshot analysis. Use trailmark or trailmark-structural.
  • Text-diff review only. Use differential-review.
  • Full vulnerability discovery. Use an audit or bug-finding workflow.
  • One static finding. Use trailmark-finding-triage.
  • Tooling is unavailable and the user wants manual review only.

Rationalizations to Reject

RationalizationWhy It Is WrongRequired Action
"The line diff is small, so no graph gate is needed"Small changes can create new call pathsCompare before/after graphs
"Graph gate passed, so the PR is secure"The gate only checks structural regressionsStill perform line-level review
"Trailmark failed, so pass the gate"Tool failure is unknown risk, not successEmit UNKNOWN
"Tests pass, so removed validation is fine"Tests may miss affected entrypoint pathsReview the removed path manually
"Only new code matters"Removed auth, validation, and callers can be higher risk than additionsReview removals and path changes

Workflow

Review Gate Progress:
- [ ] Step 1: Resolve before/after inputs
- [ ] Step 2: Build graph-evolution evidence
- [ ] Step 3: Normalize structural changes
- [ ] Step 4: Apply gate rules
- [ ] Step 5: Emit review packet and actions

Step 1: Resolve Inputs

Accept two refs, a branch name, a commit range, or before/after directories. Do not check out branches unnecessarily. Prefer git diff, git show, and git worktrees, following the graph-evolution snapshot workflow.

Step 2: Build Graph Evidence

Run graph-evolution or equivalent Trailmark before/after graph analysis. Both snapshots must run engine.preanalysis() so taint, privilege-boundary, blast-radius, complexity, and entrypoint signals are available.

Record Trailmark version and any feature probes. If graph construction fails, emit UNKNOWN.

Step 3: Normalize Changes

Normalize evidence into:

  • added, removed, and modified nodes
  • added and removed edges
  • entrypoint set changes
  • taint membership changes
  • privilege-boundary membership changes
  • blast-radius changes
  • complexity changes
  • newly reachable sensitive sinks
  • unresolved, proxy, or dynamic edge changes

Step 4: Apply Gate Rules

Apply the rules in references/gate-rules.md. Gate verdicts are:

VerdictMeaning
FAILA high-risk structural regression needs review before acceptance
WARNA meaningful graph change needs reviewer attention
PASSNo configured structural gate fired
UNKNOWNTrailmark failed or evidence is too incomplete

Step 5: Emit Packet

Write the packet using references/output-format.md, then hand it to the branch reviewer. Use references/review-integration.md when combining this packet with differential-review or another PR review process.

Requirements

  • Never mutate the user's working branch while comparing refs.
  • Never report PASS when Trailmark failed.
  • Separate graph evidence from manual security judgment.
  • Include exact changed nodes or paths for every FAIL and WARN.
  • Include limitations when parser, proxy, unresolved-call, or dynamic-dispatch uncertainty affects the verdict.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Trailmark Review Gate AI skill do?

Runs a Trailmark structural review gate over a branch, pull request, fix commit, release diff, or git ref range to detect new entrypoints, new tainted paths, removed validation or authorization calls, privilege-boundary drift, blast-radius growth, complexity growth, and newly reachable sensitive sinks. Use when reviewing a PR, branch, remediation commit, or release diff where graph-level security regressions should be checked before merge.

Why use Trailmark Review Gate on TypingMind?

Because you install it once and use it with any model. Trailmark Review Gate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trailmark Review Gate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/trailofbits/skills/tree/main/plugins/trailmark/skills/trailmark-review-gate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Trailmark Review Gate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trailmark Review Gate?

As many as you like. As long as a model supports skills, you can use Trailmark Review Gate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trailmark Review Gate AI skill free?

Yes. It is published on GitHub by trailofbits under the CC-BY-SA-4.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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