Trailmark summary
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npx -y skills add bg-szy/TOP-SKILLS --skill trailmark-summaryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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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.
SKILL.md
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Trailmark Summary
Runs trailmark analyze --language auto --summary on a target directory.
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.
Step 2: Detect languages with Trailmark's parse API.
python3 - "{args}" <<'PY'
import json
import sys
from trailmark.parse import detect_languages
print(json.dumps(detect_languages(sys.argv[1])))
PY
If the import fails, rerun the same snippet with uv run 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.
Gives 0 of the 12 instructions most note taking skills give
Counted across 686 of the 876 authors here whose files we hold, read 2026-08-06
- include a visual element on every slidein 44 of 686, across 13 files
- use wikilinks for internal vault linksin 35 of 686, across 11 files
- commit to a single visual motif across every slidein 34 of 686, across 9 files
- read pptxgenjs guide before creating presentations from scratchin 30 of 686, across 6 files
- keep 0.5 inch minimum marginsin 30 of 686, across 7 files
- use subagents to visually inspect rendered slidesin 30 of 686, across 6 files
- re-verify affected slides after every fixin 27 of 686, across 5 files
- run content QA checks before declaring successin 26 of 686, across 3 files
- Use Markdown links for external URLs onlyin 26 of 686, across 10 files
- pick a bold topic specific color palettein 24 of 686, across 2 files
- read editing guide before editing existing presentationsin 23 of 686, across 1 file
- use one dominant color across all slidesin 23 of 686, across 1 file
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.