Prismer execution contract

This is the uniquely named prismer-codebase-inspection skill, adapted from Hermes. Use the actual tools exposed by the executing host; examples using terminal, process, delegate_task, vision_analyze or browser_* are not tool registrations. Missing dependencies do not hide this skill. Report command startup, version, account/permissions and task-specific live verification separately. Use task-owned artifact paths and existing user authorization; do not change shared accounts, Runtime/provider configuration, global security settings or unrelated work. See NOTICE.md and LICENSE for resource provenance. Runtime availability and upstream-entry suppression are owned by the integration layer.

Codebase Inspection

Create TASK_TOOL_DIR with a task-owned temporary directory before installing. Use the returned venv executable path in all examples, record the resolved version, and never swallow install errors. No system Python modifications. LOC is inventory, not an architecture quality score; exclude generated/mirrored catalogs explicitly.

Analyze repositories for lines of code, language breakdown, file counts, and code-vs-comment ratios using pygount.

When to Use

• User asks for LOC (lines of code) count
• User wants a language breakdown of a repo
• User asks about codebase size or composition
• User wants code-vs-comment ratios
• General "how big is this repo" questions

Prerequisites

python3 -m venv "$TASK_TOOL_DIR/venv"
"$TASK_TOOL_DIR/venv/bin/python" -m pip install pygount
"$TASK_TOOL_DIR/venv/bin/pygount" --version
# For this shell only, so subsequent pygount examples use this isolated install.
export PATH="$TASK_TOOL_DIR/venv/bin:$PATH"

1. Basic Summary (Most Common)

Get a full language breakdown with file counts, code lines, and comment lines:

cd /path/to/repo
pygount --format=summary \
  --folders-to-skip=".git,node_modules,venv,.venv,__pycache__,.cache,dist,build,.next,.tox,.eggs,*.egg-info" \
  .

IMPORTANT: Always use --folders-to-skip to exclude dependency/build directories, otherwise pygount will crawl them and take a very long time or hang.

2. Common Folder Exclusions

Adjust based on the project type:

# Python projects
--folders-to-skip=".git,venv,.venv,__pycache__,.cache,dist,build,.tox,.eggs,.mypy_cache"

# JavaScript/TypeScript projects
--folders-to-skip=".git,node_modules,dist,build,.next,.cache,.turbo,coverage"

# General catch-all
--folders-to-skip=".git,node_modules,venv,.venv,__pycache__,.cache,dist,build,.next,.tox,vendor,third_party"

3. Filter by Specific Language

# Only count Python files
pygount --suffix=py --format=summary .

# Only count Python and YAML
pygount --suffix=py,yaml,yml --format=summary .

4. Detailed File-by-File Output

# Default format shows per-file breakdown
pygount --folders-to-skip=".git,node_modules,venv" .

# Sort by code lines (pipe through sort)
pygount --folders-to-skip=".git,node_modules,venv" . | sort -t$'\t' -k1 -nr | head -20

5. Output Formats

# Summary table (default recommendation)
pygount --format=summary .

# JSON output for programmatic use
pygount --format=json .

# Pipe-friendly: Language, file count, code, docs, empty, string
pygount --format=summary . 2>/dev/null

6. Interpreting Results

The summary table columns:

• Language — detected programming language
• Files — number of files of that language
• Code — lines of actual code (executable/declarative)
• Comment — lines that are comments or documentation
• % — percentage of total

Special pseudo-languages:

• __empty__ — empty files
• __binary__ — binary files (images, compiled, etc.)
• __generated__ — auto-generated files (detected heuristically)
• __duplicate__ — files with identical content
• __unknown__ — unrecognized file types

Pitfalls

1. Always exclude .git, node_modules, venv — without --folders-to-skip, pygount will crawl everything and may take minutes or hang on large dependency trees.
2. Markdown shows 0 code lines — pygount classifies all Markdown content as comments, not code. This is expected behavior.
3. JSON files show low code counts — pygount may count JSON lines conservatively. For accurate JSON line counts, use wc -l directly.
4. Large monorepos — for very large repos, consider using --suffix to target specific languages rather than scanning everything.