Generate skill from various sources

VerifiedCaution

CLI tool to generate a SKILL.md file from MCP, README, or OpenAPI. Options include --platform and --dry-run.

Sby Skills Guide Bot
DevelopmentIntermediate
7/22/2026
Claude Code
#skill-generation#scaffolding#mcp#openapi#codegen

Recommended for

Automated summary

Generates a new SKILL.md scaffold from an MCP server config, a README, or an OpenAPI spec via the `ct generate skill` CLI, then validates it and rebuilds the index.

Strengths

  • Supports three distinct input sources: MCP config, README, and OpenAPI spec
  • Useful flags such as `--dry-run` to preview output and `--examples N` to control how many examples are generated
  • Includes post-generation steps: validation via `validate_skill.py` and index rebuild via `build_index.py`
  • Lets you target a destination platform (anthropic, openai, universal)

Limitations

  • Relies on an external `ct` CLI that must be installed and available
  • The generated SKILL.md requires manual review and correction for accuracy
  • Does not address updating an existing skill or handling generation failures
When to use it

Use it to bootstrap a new skill quickly from an existing API, spec, or README instead of writing the SKILL.md by hand.

When not to use it

Avoid it when authoring a skill manually or when your source is not an MCP config, a README, or an OpenAPI spec.

Security analysis

Caution
Quality score84/100

The skill uses legitimate file-generation and bash tooling, with no destructive commands, obfuscation, credential exfiltration, or curl|sh patterns. However, it executes an external CLI and writes files, so it warrants caution rather than a fully safe rating.

Findings
  • •Invokes bash commands and an external `ct` CLI to generate files under `./skills/<slug>/` without requiring confirmation, though `--dry-run` is available.
  • •Reads input files such as MCP configs, READMEs, and OpenAPI specs that may contain sensitive configuration; generated output could inadvertently include secrets if the source does.
  • •Does not declare allowed-tools despite including executable bash snippets.
How this analysis is made

Examples

From an MCP config
Generate a skill named github-tools from my MCP config at ./configs/github-mcp.json into ./skills/github-tools/, but do a dry run first so I can review the output.
From an OpenAPI spec
Create a skill called stripe-api from ./specs/stripe-openapi.json with 5 examples, then validate it with tooling/validate_skill.py.
From a README
Build a skill called acme-sdk from ./README.md, add the CHANGELOG, and rebuild the index when you're done.

Generate a new skill from various sources.

Arguments: $ARGUMENTS (source type and path)

From MCP Server

ct generate skill --from-mcp <config.json> --name <skill-name> --output ./skills/<slug>/

From README

ct generate skill --from-readme <README.md> --name <skill-name> --output ./skills/<slug>/

From OpenAPI Spec

ct generate skill --from-openapi <openapi.json> --name <skill-name> --output ./skills/<slug>/

Options

  • --platform anthropic|openai|universal - Target platform (default: universal)
  • --dry-run - Preview without writing files
  • --examples N - Number of examples to generate (default: 3)

After generation:

  1. Review generated SKILL.md for accuracy
  2. Validate: python tooling/validate_skill.py skills/<slug>/
  3. Add CHANGELOG.md if not generated
  4. Rebuild index: python tooling/build_index.py

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/generate-skill-from-various-sources-mrwakdvb/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/generate-skill-from-various-sources-mrwakdvb' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/generate-skill-from-various-sources-mrwakdvb/download' --output '.skill-downloads/generate-skill-from-various-sources-mrwakdvb/SKILL.md.part' && mv '.skill-downloads/generate-skill-from-various-sources-mrwakdvb/SKILL.md.part' '.skill-downloads/generate-skill-from-various-sources-mrwakdvb/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

This file does not provide a usable name/description header for this native procedure. It remains available to download and inspect; use the manual method below.

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/generate-skill-from-various-sources-mrwakdvb/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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