Trailmark Summary

SkillDev tools

Lets your agent scan a codebase and report its languages, entry points, and dependencies.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Trailmark Summary skill

About this capability

Runs a Trailmark summary analysis on a codebase. Returns auto-detected languages, entry point count, and dependency list. Use when vivisect or galvanize needs a quick structural overview. Triggers: trailmark summary, code summary, structural overview.

What this skill tells your AI

The instructions your AI receives, as published by trailofbits/skills in plugins/trailmark/skills/trailmark-summary/SKILL.md and read by ahel’s review.

Runs trailmark analyze --language auto --summary on a target directory. This is a v0.2-safe workflow; do not require Trailmark 0.4.0 just to produce a summary.

When to Use

  • Vivisect Phase 0 needs a quick structural overview before decomposition
  • Galvanize Phase 1 needs detected languages and entry point count
  • Quick orientation on an unfamiliar codebase before deeper analysis

When NOT to Use

  • Full structural analysis with all passes needed (use trailmark-structural)
  • Detailed code graph queries (use the main trailmark skill directly)
  • You need hotspot scores or taint data (use trailmark-structural)

Rationalizations to Reject

RationalizationWhy It's WrongRequired Action
"I can read the code manually instead"Manual reading misses parser-based language detection, dependency data, and entry point enumerationInstall and run trailmark
"Language detection doesn't matter"Wrong language selection produces empty or partial analysisUse Trailmark's parser-based detection or --language auto
"Partial output is good enough"Missing any of the three required outputs (detected languages, entry points, dependencies) means incomplete analysisVerify all three are present
"Tool isn't installed, I'll skip it"This skill exists specifically to run trailmarkReport the installation gap instead of skipping

Usage

The target directory is passed via the args parameter.

Execution

Step 1: Check that trailmark is available.

trailmark analyze --help 2>/dev/null || \
  uv run trailmark analyze --help 2>/dev/null

If neither command works, report "trailmark is not installed" and return. Do NOT run pip install, uv pip install, git clone, or any install command. The user must install trailmark themselves.

Optionally record the version if the installed build supports it:

trailmark --version 2>/dev/null || uv run trailmark --version 2>/dev/null || true

Do not fail if the version command is missing; older v0.2.x builds may still support the summary workflow.

Step 2: Detect languages with Trailmark's parse API.

python3 - "{args}" <<'PY'
import json
import sys

try:
    from trailmark.parse import detect_languages  # canonical location since 0.3.x
except ModuleNotFoundError:
    # v0.2.x predates trailmark.parse; the same function lives in query.api
    from trailmark.query.api import detect_languages

print(json.dumps(detect_languages(sys.argv[1])))
PY

If the import fails, rerun the same snippet with uv run --with trailmark python - "{args}". If the result is [], report "Trailmark found no supported languages under target" and return.

Step 3: Run the summary with auto-detection.

trailmark analyze --language auto --summary {args} 2>&1 || \
  uv run trailmark analyze --language auto --summary {args} 2>&1

Step 4: Verify the output.

The output must include ALL THREE of:

  1. Detected languages from Step 2
  2. Entrypoints: line from the summary output
  3. Dependencies: line from the summary output

If any are missing, report the gap. Do not fabricate output.

Return the detected language list plus the full Trailmark summary output. If a version string was available, include it in the returned metadata.

Signals

GitHub stars
7k
Forks
604
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
trailmark-summary
Source
github.com/trailofbits/skills