skill-audit/agent-audit's Step 1 resolved vale-wrap.sh/.vale.ini via `git rev-parse --show-toplevel`, which returns whichever repo the skill happens to run in. Inside ai-development that works; in any external repo that installs kyberforge@holocron as a plugin, it resolves to that repo's own root, which has no .vale.ini — the prefilter silently fell back to full LLM judgment. ADR-0013 named this as a deliberately deferred gap. Vale's config/styles/wrapper now ship inside the plugin itself: a canonical copy in agent-audit/assets/vale/ (Kyberforge + KyberforgeCopilot, the superset agent-audit needs) and a smaller duplicate in skill-audit/assets/vale/ (Kyberforge only) — per the no-cross-skill-path rule already established for plugin cache-installs. Both skills resolve these relative to their own directory, same as scripts/validate.sh already does. A new root .pre-commit-hooks.yaml exposes both copies plus skill-size-check so any external repo can enforce the same rules via `repo: <this-repo-url>, rev: <tag>` in its own pre-commit config, independent of Claude Code entirely — the same mechanism covers CI. This repo's own pre-commit hook now consumes the identical plugin-bundled copies via repo: local (not a third root copy, and not a pinned self-reference, which would lint working-tree edits against the last tagged release instead of the change being made). Split into vale-audit-prefilter-skill/-agent hooks after confirming, by diffing the full corpus against both old and new config before deleting the old files, that one combined hook pointed at only one copy silently 0-file- skips the other file type. scripts/check-vale-style-sync.sh guards the two copies against drift, wired at pre-push alongside check-manifests. ADR: 0014
scripts/
Executable code bundled with this skill. Agents run scripts in this directory to perform repeatable operations rather than reinventing the logic each run.
When to add a script
Add a script when agents independently reinvent the same logic across runs — building the same parser, chart, or validation routine from scratch each time. Bundle it here once, tested and reliable.
Script requirements (agentskills.io)
Scripts must be designed for non-interactive, agentic execution:
- No interactive prompts — agents run in non-interactive shells. Accept all input via flags, env vars, or stdin. A script that blocks on TTY input hangs indefinitely.
- Expose
--help— this is how agents learn your script's interface. Keep the output concise; it enters the agent's context window. - Structured output — write data (JSON, CSV, TSV) to stdout. Write progress, warnings, and diagnostics to stderr.
- Idempotent — prefer "create if not exists" over "create and fail on duplicate". Agents may retry on failure.
- Meaningful exit codes —
0for success, non-zero for failure. Use distinct codes for different failure types; document them in--help. - Dry-run support — add
--dry-runfor destructive operations.
Self-contained scripts
Bundle dependencies inline so the agent can run the script with a single command.
Python (PEP 723 + uv):
# /// script
# dependencies = ["requests>=2.31,<3"]
# requires-python = ">=3.11"
# ///
import requests
uv run scripts/my-script.py
If no scripts are needed
Delete this README and the scripts/ directory entirely.