Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/lifangda/claude-plugins/lintgit clone --depth 1 https://github.com/lifangda/claude-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00000 | $0.00478 |
| Opus 5 | $0.00000 | $0.00239 |
| Sonnet 5 | $0.00000 | $0.00096 |
| Haiku 4.5 | $0.00000 | $0.00048 |
Grade A, and why
lint scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to lint — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Python Linter
Run Python code linting and formatting tools.
Purpose
This command helps you maintain code quality using Python's best linting and formatting tools.
Usage
/lint
What this command does
- Runs multiple linters (flake8, pylint, black, isort)
- Provides detailed feedback on code quality issues
- Auto-fixes formatting where possible
- Checks type hints if mypy is configured
Example Commands
Black (code formatting)
# Format all Python files
black .
# Check formatting without changing files
black --check .
# Format specific file
black src/main.py
flake8 (style guide enforcement)
# Check all Python files
flake8 .
# Check specific directory
flake8 src/
# Check with specific rules
flake8 --max-line-length=88 .
isort (import sorting)
# Sort imports in all files
isort .
# Check import sorting
isort --check-only .
# Sort imports in specific file
isort src/main.py
pylint (comprehensive linting)
# Run pylint on all files
pylint src/
# Run with specific score threshold
pylint --fail-under=8.0 src/
# Generate detailed report
pylint --output-format=html src/ > pylint_report.html
mypy (type checking)
# Check types in all files
mypy .
# Check specific module
mypy src/models.py
# Check with strict mode
mypy --strict src/
Configuration Files
Most projects benefit from configuration files:
.flake8
[flake8]
max-line-length = 88
exclude = .git,__pycache__,venv
ignore = E203,W503
pyproject.toml
[tool.black]
line-length = 88
[tool.isort]
profile = "black"
Best Practices
- Run linters before committing code
- Use consistent formatting across the project
- Fix linting issues promptly
- Configure linters to match your team's style
- Use type hints for better code documentation
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 111 lines · 0 tokens per session scan A 571456f6f3bb
lint is a command published in the GitHub repository lifangda/claude-plugins (43 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 478 tokens. A static security scan graded it A with 0 findings. It is 100% identical to lint, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.