trailmark-summary
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.
Install
npx skills add https://github.com/trailofbits/skills/tree/main/plugins/trailmark/skills/trailmark-summary
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install trailofbits-skills@llmmart
git clone https://github.com/trailofbits/skills.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole trailofbits/skills collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
Trailmark Summary
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
trailmarkskill directly) - You need hotspot scores or taint data (use
trailmark-structural)
Rationalizations to Reject
| Rationalization | Why It's Wrong | Required Action |
|---|---|---|
| "I can read the code manually instead" | Manual reading misses parser-based language detection, dependency data, and entry point enumeration | Install and run trailmark |
| "Language detection doesn't matter" | Wrong language selection produces empty or partial analysis | Use 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 analysis | Verify all three are present |
| "Tool isn't installed, I'll skip it" | This skill exists specifically to run trailmark | Report 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:
- Detected languages from Step 2
Entrypoints:line from the summary outputDependencies: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.
Files (skills)
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agents
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openai.yaml 238 B
interface: display_name: "Trailmark Summary" short_description: "Summarize a codebase with Trailmark graph analysis" icon_small: "assets/trail-of-bits-mark.svg" icon_large: "assets/trail-of-bits-mark.svg" brand_color: "#D83A34"
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assets
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trail-of-bits-mark.svg 3 KB · in bundle
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SKILL.md 3.6 KB
--- name: trailmark-summary description: "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." allowed-tools: Bash Read Grep Glob --- # Trailmark Summary 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 | Rationalization | Why It's Wrong | Required Action | |-----------------|----------------|-----------------| | "I can read the code manually instead" | Manual reading misses parser-based language detection, dependency data, and entry point enumeration | Install and run trailmark | | "Language detection doesn't matter" | Wrong language selection produces empty or partial analysis | Use 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 analysis | Verify all three are present | | "Tool isn't installed, I'll skip it" | This skill exists specifically to run trailmark | Report the installation gap instead of skipping | ## Usage The target directory is passed via the `args` parameter. ## Execution **Step 1: Check that trailmark is available.** ```bash 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: ```bash 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.** ```bash 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.** ```bash 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.
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