hectorpulido/pequeroku/authoring-tools
Claude Code and agent skill by hectorpulido/pequeroku
- community
Checking that the SKILL.md file is still in the repository.
Create a custom tool for this workspace — a named, schema'd command that runs in the VM and the agent can call. Use when the user wants a reusable operation exposed as a first-class tool, or you spot a repeatable VM workflow worth wrapping.
Install
npx vskill@latest install hectorpulido/pequeroku/authoring-toolsSKILL.md
Authoring a custom tool
A custom tool turns a command into a first-class tool the agent can call by name, with a typed argument schema — unlike a one-off bash call. It runs INSIDE this VM (the same sandbox bash uses), so it grants no new powers; it just packages a workflow cleanly.
Where custom tools live
/app/.pequenin/tools/<name>/ ├── tool.json # the manifest (required) └── <your script> # whatever command runs (run.py, run.sh, ...)
One folder per tool. Bundle any helper files in the same folder.
tool.json
{ "name": "run-linter", "description": "Run ruff on a path and return the findings. Use before committing Python.", "parameters": { "type": "object", "properties": { "path": { "type": "string", "description": "File or dir to lint." } }, "required": ["path"] }, "command": "python3 run.py" }
Fields:
name— REQUIRED. Lowercase letters/digits with single hyphens
(^[a-z0-9]+(-[a-z0-9]+)*$), 1–64 chars, and it MUST equal the folder name.
description— REQUIRED. Say WHEN to use the tool and what it returns — this is what
the agent reads to decide whether to call it.
parameters— JSON Schema (an object) describing the arguments the agent passes.
Defaults to {"type":"object","properties":{}} if omitted.
command— REQUIRED. The command to run (e.g.python3 run.py,bash run.sh,
node run.js). It runs with the tool's folder as the working directory.
The contract: args in on STDIN, result out on STDOUT
When the agent calls the tool, your command runs in the tool's folder and receives the validated arguments as a single JSON object on stdin. Whatever it writes to stdout/stderr is returned to the agent. Example run.py:
import json, subprocess, sys args = json.load(sys.stdin) # e.g. {"path": "app/"} out = subprocess.run(["ruff", "check", args["path"]], capture_output=True, text=True) print(out.stdout or out.stderr)
How to create one
- Pick a kebab-case
<name>. write/app/.pequenin/tools/<name>/tool.jsonwith the manifest above.writethe script yourcommandruns, in the same folder.- The tool is discovered on the NEXT turn (discovery runs once, at turn start). It
then appears in your toolset and you can call it by name.
Limits and gotchas
- Runs FOREGROUND, ~25s cap (same as foreground
bash). For long work, have the
command background it itself (setsid, nohup … &) and return quickly.
- Runs with the agent's VM privileges (root in the sandbox) — same as
bash. Don't
put secrets in tool.json.
name!= folder, invalid JSON, or a missingdescription/command→ the tool is
silently skipped (check the next turn's toolset to confirm it loaded).
- Custom tools are VM files: they persist with the workspace but are wiped on a
workspace reset.
- A custom tool can't shadow a built-in tool (the built-in wins on a name clash).
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingsource/web_service/ai_services/minicode/builtin_skills/authoring-tools/SKILL.md
Popularity
- Repository stars
- 69
- Repository forks
- 10
- 7-day trend score
- 21
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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