trailmark-summary

SKILL.md

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.

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 output

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.