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Create Skill

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dotnet
create-skill

Scaffolds new agent skills for the dotnet/skills repository. Use when creating a new skill, generating SKILL.md files, writing a skill description that the runtime will actually route to, or setting up skill directory structures. Handles frontmatter generation, section templates, and validation guidance. Do not use for fixing a skill that already fails its evaluation (use improve-skill-quality) or for writing eval.yaml (use create-skill-test).

Overview

Publisherdotnet
Repositoryskills
Skill namecreate-skill
Stars
5.5K
Forks
420
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Create Skill 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/dotnet/skills/tree/main/.agents/skills/create-skill
  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/dotnet/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/.agents/skills/create-skill .claude/skills/create-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Skill 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 Create Skill 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 Create Skill 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.

Create Skill

This skill helps you scaffold new agent skills that conform to the Agent Skills specification and the dotnet/skills repository conventions.

When to Use

  • Creating a new skill from scratch
  • Generating a SKILL.md file with proper frontmatter
  • Setting up the skill directory structure with optional folders
  • Ensuring compliance with agentskills.io specification

When Not to Use

  • Modifying existing skills (edit directly instead)
  • Diagnosing or fixing a skill that fails its evaluation (use improve-skill-quality)
  • Writing the skill's eval.yaml (use create-skill-test)
  • Creating custom agents (use the agents/ directory pattern)

Inputs

InputRequiredDescription
Skill nameYesLowercase, alphanumeric, hyphens only (e.g., code-review, ci-triage)
DescriptionYesWhat the skill does and when agents should use it (1-1024 chars)
PurposeYesOne paragraph describing the outcome
Workflow stepsRecommendedNumbered steps the agent should follow

Workflow

Step 1: Validate the skill name

Ensure the name:

  • Contains only lowercase letters, numbers, and hyphens
  • Does not start or end with a hyphen
  • Does not contain consecutive hyphens
  • Is between 1-64 characters

Step 2: Write the description — it is the router

The description is the only text the runtime sees when deciding whether to load the skill. A perfect body behind a weak description never runs.

yaml
---
name: <skill-name>
description: <what it does>. USE FOR: <symptoms, error codes, artifact names, quoted user requests>. DO NOT USE FOR: <nearby-but-wrong intents, with the skill that owns them>.
---
  • Lead with an action verb and use the user's own words: symptoms, error codes (CS1501, MSTEST0014), artifact names (.testsettings, binlog), and requests phrased as a developer would type them.
  • Partition against sibling skills on the real discriminator, not the topic. "Does the abstraction already exist?" separates two skills; "testing" does not. Add the matching exclusion to both siblings.
  • Claim the ambiguous words that would otherwise route to a sibling. If prompts say "review my tests" and a sibling owns "review", say so explicitly.
  • Check every DO NOT USE FOR clause against the scenarios the skill exists to serve — an exclusion like "already on v3" can lock out the post-upgrade fixes that are the skill's purpose.
  • Budget: 1,024 characters per description, and the whole plugin's rendered skill menu is also budgeted. A helper skill users should never invoke directly can set disable-model-invocation: true to free menu space while staying invocable by name.

Step 3: Write for delta over the baseline model

Every skill is scored head-to-head against the same model with no skill loaded. Content the model already produces unaided is worth zero; content that makes it slower or more hedged is worth less than zero. See improve-skill-quality/references/writing-for-baseline-delta.md for the full evidence.

DoInstead of
Encode the decision the model would otherwise get wrongRestating API signatures it already reproduces
"When A, do B, never C, verify D" tablesLists of plausible alternatives
A concrete output contract (exact command, verdict line, findings table)"Consider…", "you may want to…"
Scale output structure to input sizeA 12-section dashboard for an 8-test suite
Stop-conditions that prevent over-applyingActing before measuring, rewriting working code
Instructing the agent to discover repo pathsMarking discoverable paths as required inputs
Reporting restore/build/test failures truthfullyClaiming success after a failed command
Verifying load-bearing API claims by compiling or probingTrusting a source read
Gating rare or expensive paths behind references/One large SKILL.md carrying every path

Do not over-correct: a skilled answer shorter and less actionable than the baseline's still loses.

Step 4: Create the skill directory

plugins/<plugin>/skills/<skill-name>/
└── SKILL.md

Step 5: Generate SKILL.md with frontmatter

Create the file with the frontmatter drafted in Step 2.

Step 6: Add body content sections

Include these recommended sections:

  1. Purpose: One paragraph describing the outcome
  2. When to Use: Bullet list of appropriate scenarios
  3. When Not to Use: Boundaries and exclusions
  4. Inputs: Table of required and optional inputs
  5. Workflow: Numbered steps with checkpoints
  6. Validation: How to confirm the skill worked correctly
  7. Common Pitfalls: Known traps and how to avoid them

Step 7: Add optional directories (if needed)

plugins/<plugin>/skills/<skill-name>/
├── SKILL.md
├── scripts/       # Executable code agents can run
├── references/    # Additional documentation loaded on demand
└── assets/        # Templates, images, data files

Reference bundled files with paths relative to the directory that contains SKILL.md, such as references/details.md or scripts/validate.ps1. Do not tell the agent to search for the skill's installation directory. If a missing bundled file reduces the result quality, allow one listing of the known bundled-file directory and require the agent to report the reduced coverage.

Step 8: Update CODEOWNERS

Add entries in .github/CODEOWNERS for the new skill and its test directory:

/plugins/<plugin>/skills/<skill-name>/  @owner-team
/tests/<plugin>/<skill-name>/           @owner-team

Match the owner pattern used by sibling skills in the same plugin.

Step 9: Validate the skill

  • Confirm frontmatter fields are valid
  • Ensure SKILL.md is under 500 lines
  • Check that file references use relative paths
  • Verify instructions are actionable and specific
  • Run dotnet run --project eng/skill-validator/src/SkillValidator.csproj -- check --plugin ./plugins/<plugin>

Step 10: Add the eval

A skill without an eval.yaml has no evidence that it improves on the baseline. Use create-skill-test to add one in the same pull request, and size it for statistical power — an eval below five distinct stimuli can never return a passing verdict.

The exception is a helper skill with disable-model-invocation: true: the model cannot self-activate it, so an activation-graded eval compares two identical arms. Cover it through the evals of the skills that load it instead.

SKILL.md Template

Use this template when creating a new skill:

markdown
---
name: <skill-name>
description: <1-1024 char description of what the skill does and when to use it>
---

# <Skill Title>

<One paragraph describing the skill's purpose and outcome.>

## When to Use

- <Scenario 1>
- <Scenario 2>

## When Not to Use

- <Exclusion 1>
- <Exclusion 2>

## Inputs

| Input | Required | Description |
|-------|----------|-------------|
| <input-name> | Yes/No | <description> |

## Workflow

### Step 1: <Action>

<Instructions for this step>

### Step 2: <Action>

<Instructions for this step>

## Validation

- [ ] <Verification step 1>
- [ ] <Verification step 2>

## Common Pitfalls

| Pitfall | Solution |
|---------|----------|
| <Problem> | <How to avoid or fix> |

Validation Checklist

After creating a skill, verify:

  • Skill name matches directory name exactly
  • Skill name is lowercase with hyphens only
  • Description is non-empty and under 1024 characters
  • SKILL.md body is under 500 lines
  • Instructions are specific and actionable
  • Bundled-file paths are relative to the directory that contains SKILL.md
  • Missing bundled files cannot cause silent degradation
  • Workflow has numbered steps with clear checkpoints
  • Validation section exists with observable success criteria
  • No secrets, tokens, or internal URLs included
  • .github/CODEOWNERS has entries for the new skill and its test directory
  • The description names concrete triggers and excludes the nearest sibling skills
  • Every section changes a decision the unskilled model would otherwise get wrong
  • The skill states when not to act, and what a truthful failure report looks like
  • An eval.yaml exists and clears the distinct-stimulus floor (or the skill is disable-model-invocation: true and covered through its consumers)

Common Pitfalls

PitfallSolution
Name contains uppercase lettersUse only lowercase: code-review not Code-Review
Description is vagueInclude what it does AND when to use it
Instructions are ambiguousUse numbered steps with concrete actions
Missing validation stepsAdd checkpoints that verify success
SKILL.md too longMove detailed content to references/ files
Hardcoded environment assumptionsDocument requirements in compatibility field
Missing CODEOWNERS entryAdd entries for both /plugins/<plugin>/skills/<skill-name>/ and /tests/<plugin>/<skill-name>/ matching sibling skills' owner pattern
Skill restates what the model already knowsCut it; a skill is scored as a delta over the unskilled model
Discoverable paths listed as required inputsTell the agent to discover them, or it will stop and ask the user
Description partitioned by topic against a siblingPartition on the real discriminator and exclude on both sides
Exclusion clause blocks the skill's own use casesRe-read every "do not use for" clause against real workflow phases
Skill added without an evalAdd eval.yaml in the same PR; unevaluated skills carry no evidence

References

Frequently asked questions

What does the Create Skill AI skill do?

Scaffolds new agent skills for the dotnet/skills repository. Use when creating a new skill, generating SKILL.md files, writing a skill description that the runtime will actually route to, or setting up skill directory structures. Handles frontmatter generation, section templates, and validation guidance. Do not use for fixing a skill that already fails its evaluation (use improve-skill-quality) or for writing eval.yaml (use create-skill-test).

Why use Create Skill on TypingMind?

Because you install it once and use it with any model. Create Skill 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 Create Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dotnet/skills/tree/main/.agents/skills/create-skill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Create Skill?

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 Create Skill?

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

Is the Create Skill AI skill free?

Yes. It is published on GitHub by dotnet 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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