Is vigilante-issue-implementation-on-python safe to install?
SaferSkills independently audited vigilante-issue-implementation-on-python (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
description: Implement a GitHub issue end-to-end when Vigilante dispatches work for a Python repository with idiomatic tooling and security guidance.
Vigilante Python Issue Implementation
Focus
Read the prompt for detected tech stacks, process hints, and Python security guidance before changing code.
Follow idiomatic Python conventions already established by the repository and keep changes scoped to the issue.
Prefer the repository's existing environment, dependency, formatting, linting, typing, and test workflows over inventing a new stack.
Python Tooling Workflow
Environment: use the repository's documented bootstrap or environment workflow first. When no repo-specific workflow exists, prefer isolated environments such as venv rather than ad hoc global installs.
Formatting and linting: run the repository's established formatter and linter for touched files. When the repository already uses Ruff, prefer ruff format and ruff check; when it uses Black, use black. Do not introduce repo-wide formatting churn unrelated to the issue.
Typing: run the repository's existing typing checks when present, such as mypy, pyright-style tooling, or equivalent configured commands.
Testing: run targeted pytest or repo-standard test commands for the changed area first, then broaden scope when needed.
Dependency and package security: when dependency or packaging changes are involved, run repo-standard audit tooling. Use pip-audit when it is already part of the repo workflow or otherwise clearly available and relevant.
Dependencies: prefer standard library modules when they cover the need. Keep dependency manifests and lockfiles consistent when adding or updating packages.
Idiomatic Python
Follow existing project conventions for layout, imports, and naming instead of forcing a new style.
Prefer small, explicit functions, early returns, and straightforward exception handling.
Add or update docstrings only where the repository already expects them or where a public API change needs clear documentation.
Avoid broad cleanup or modernization unrelated to the issue.
Security
Prefer secrets over random for security-sensitive values.
Avoid unsafe pickle usage or deserializing untrusted data with Python-native object loaders.
Be careful with subprocess: prefer explicit argument lists, avoid shell=True unless required and safely constrained, and validate any external input passed to commands.
Treat file paths and untrusted input defensively to avoid traversal, injection, and unintended file access.
Do not store secrets, tokens, or credentials in source files.
Workflow
Follow the base vigilante-issue-implementation workflow for issue comments, validation, push, and PR creation, including stacked base-branch detection (Base branch: directive in the issue body).
Use vigilante commit for all commit-producing operations. Do not use git commit or GitHub CLI commit flows directly.
Any commit or amend must preserve the user's existing git author, committer, and signing configuration. Commit on behalf of the user and do not overwrite git config with a coding-agent identity.
Do not add Co-authored by: trailers or any other agent attribution for Codex, Claude, Gemini, or similar coding-agent identities.
Repository Overrides
Repository-specific instructions (AGENTS.md, README.md, CI config, tool config files) remain authoritative when they are more specific than the generic Python guidance in this skill.