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Skill Creator Plus

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robonuggets
skill-creator-plus

Audits, creates and improves Agent Skills (folders with a SKILL.md) against Anthropic's skill authoring best practices, the Claude Code skills docs and the prompting guides for newer models such as Claude Fable 5 and Opus 5.5. Audit mode reports every rule as pass, fail or not applicable, with file and line evidence and a proposed fix, and changes nothing until the user approves. Use when the user asks to audit, review, check or score a skill or a folder of skills, to create a new skill or turn a repeated workflow into one, to improve, shorten, refactor or update an old skill for newer models, or to run the skill validator.

Overview

Publisherrobonuggets
Repositoryskill-creator-plus
Skill nameskill-creator-plus
Stars
76
Forks
12
Bundled files
13
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 13 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by robonuggets on GitHub. Read the source before you install it.

Installation

Install the Skill Creator Plus AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/robonuggets/skill-creator-plus/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/robonuggets/skill-creator-plus.git \
  .claude/skills/skill-creator-plus
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Creator Plus in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Skill Creator Plus on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Skill Creator Plus is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Skill Creator Plus

Audits, builds and improves skills so Claude takes the same process on each run. A skill is a table of contents, not a manual: the description gets it chosen, SKILL.md says what to do, and detail waits in reference files until a step needs it.

Rules for every mode

  1. Report before you change. Start from evidence: the validator's output and a full read of the skill. In AUDIT, edit nothing until the user picks which findings to fix, because a skill change alters each future run and the user owns that call. A direct request to fix a named problem is already that approval.
  2. Absorb, don't layer. Fold new guidance into the rule it refines and delete what it replaces. A good edit usually leaves the skill shorter. Write the reason, not the date, so a later editor can tell whether the rule still holds.
  3. Test before you delete. Newer models often do better with fewer instructions, but only a with-skill and without-skill run proves a line is dead weight. Method: references/testing.md, "Test before you delete".
  4. The validator is the floor. scripts/validate_skill.py checks what a script can check. The judgment rules in references/audit-checklist.md need a careful read.

Pick the mode

ModeWhenOutput
AUDITA skill or a folder of skills should be checked, scored or improvedA findings report, then only the approved edits
NEWNo skill covers the job yetA new skill folder that passes the validator and its test prompts
REFINEA skill exists and new evidence arrived: a correction, a miss, a shipped resultThe same skill, rewritten around the principle, usually shorter

"Improve this skill" means AUDIT, then REFINE with the approved changes.

AUDIT

Copy this checklist into the reply and tick it off:

text
Audit progress:
- [ ] 1 Validator run on every skill in scope
- [ ] 2 Each skill read in full: SKILL.md, references, scripts
- [ ] 3 Every checklist rule marked pass, fail or N/A, with evidence
- [ ] 4 Report written
- [ ] 5 User chose which changes to apply
- [ ] 6 Approved changes applied
- [ ] 7 Validator re-run with no new errors or warnings

Step 1. Run the validator. python3 scripts/validate_skill.py <skill-folder> for one skill, or --all <folder> for a library; then audit in full the skills the user picks, by default the five with the most errors. Add --json to parse the results. Done when you have output for every skill in scope.

Step 2. Read the skill. All of it: SKILL.md, each reference file, each script. Done when you can name the skill's job, its branches and what every file is for.

Step 3. Mark every rule. Open references/audit-checklist.md. Script rules take the validator's result; read rules need evidence you can cite as file and line. Done when no rule is unmarked.

Step 4. Write the report in the format at the end of the checklist: the table with fails first, the changes ranked by impact, then anything that needs the user's decision. The worked example in examples/ shows the bar.

Step 5. Stop and ask. End the turn with the numbered changes. Edit nothing until the user picks.

Step 6. Apply the approved changes following REFINE. Before deleting instructions as too prescriptive (rule NM1), run the test in references/testing.md.

Step 7. Re-run the validator. If it shows a new error or warning, return to Step 6.

NEW

text
New skill progress:
- [ ] 1 Evidence: the task done once without a skill, gaps noted
- [ ] 2 Three test prompts and a no-skill baseline
- [ ] 3 Shape, invocation and freedom chosen
- [ ] 4 Folder scaffolded
- [ ] 5 Frontmatter and body written
- [ ] 6 Validator clean
- [ ] 7 Tests re-run in a fresh session
- [ ] 8 Audit checklist passed
  1. Evidence. Do the task once with Claude and no skill, or read real past examples. Note what had to be explained. Done when you can list the gaps the skill must close.
  2. Tests first. Write three prompts people would type and record the no-skill result (references/testing.md). Done when the baseline is written down.
  3. Shape. Choose single file, bundle or router; who can invoke it; and the freedom for each step (references/authoring-guide.md). Done when each choice has a one-line reason.
  4. Scaffold. Run python3 scripts/init_skill.py <name> --path <skills-folder>, adding --refs, --scripts or --user-invoked as needed. It creates the folder and validates it. Done when the folder exists.
  5. Write. Description first, then the body: the most important rules at the top, a checklist with a go-back line for multi-step work, detail in linked files. Replace every [FILL: ...] placeholder. Done when nothing is left to fill.
  6. Validate. Run the validator on the folder. Fix every error; fix or justify every warning. If an error remains, return to step 5.
  7. Re-test. Run the test prompts in a fresh session with the skill on. If one fails, return to step 5.
  8. Audit. Mark the checklist rules that need a read. Done when nothing fails.

REFINE

  1. Name the evidence in one line: what happened, what the user said, what shipped.
  2. Find the principle that explains it. If you cannot name it, you are not ready to edit.
  3. Rewrite every line the principle touches and delete lines it makes redundant. If a shipped result contradicts an older rule, the shipped result wins; tell the user.
  4. Check. Run the validator. The file should not have grown; if it did, find what the new rule made redundant. If the validator shows a new error, return to step 3.

Resources

  • references/audit-checklist.md - every rule with its ID, why it matters, how to check it and its source, plus the report format and the failure modes. Open in AUDIT step 3, and before calling any skill done.
  • references/authoring-guide.md - how to write each part: frontmatter fields, description, structure, degrees of freedom, workflows, scripts, hooks, newer models. Open in NEW steps 3 to 5 and in REFINE.
  • references/testing.md - evaluations, fresh-session baselines, Claude A and B, model sweeps, test before you delete. Open in NEW steps 2 and 7, and before cutting instructions.
  • examples/pdf-helper-report.md - a finished audit report for the flawed sample skill in examples/pdf-helper/, built from the validator output in examples/pdf-helper-validator-output.txt. Open to see the bar for a report.
  • scripts/validate_skill.py - run it, do not read it. --help lists the flags.
  • scripts/init_skill.py - run it to scaffold a new skill.

Script paths are relative to this skill's folder (in Claude Code, ${CLAUDE_SKILL_DIR}). Use python3, or python on Windows. Python 3.8 or newer, standard library only, nothing to install.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Skill Creator Plus AI skill do?

Audits, creates and improves Agent Skills (folders with a SKILL.md) against Anthropic's skill authoring best practices, the Claude Code skills docs and the prompting guides for newer models such as Claude Fable 5 and Opus 5.5. Audit mode reports every rule as pass, fail or not applicable, with file and line evidence and a proposed fix, and changes nothing until the user approves. Use when the user asks to audit, review, check or score a skill or a folder of skills, to create a new skill or turn a repeated workflow into one, to improve, shorten, refactor or update an old skill for newer mode...

Why use Skill Creator Plus on TypingMind?

Because you install it once and use it with any model. Skill Creator Plus is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Skill Creator Plus in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/robonuggets/skill-creator-plus/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Skill Creator Plus?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Skill Creator Plus?

As many as you like. As long as a model supports skills, you can use Skill Creator Plus with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Skill Creator Plus AI skill free?

Yes. It is published on GitHub by robonuggets under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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