claude-command-converter
Convert Claude Code commands (.claude/commands/*.md) to standard Agent Skills (skills/*/SKILL.md). Use when migrating slash commands to portable skill format, creating skills from existing commands, or standardizing command definitions across AI runtimes.
What this skill does
# Claude Command Converter
Convert Claude Code commands to standard Agent Skills format for portability across AI coding assistants.
## When to Use
- Migrating existing `.claude/commands/*.md` files to `skills/*/SKILL.md` format.
- Creating portable skills from Claude Code-specific commands.
- Standardizing command definitions for use with Claude Code, Codex CLI, GitHub Copilot, and other runtimes.
## Inputs
- Source command file path (e.g., `.claude/commands/my-command.md`).
- Optional: target skill name (defaults to command filename without extension).
If input is missing, ask for the source command file path.
## Format Differences
### Claude Code Command Format
Location: `.claude/commands/<command-name>.md`
```yaml
---
description: Short description of the command
handoffs:
- label: Next Action
agent: other.command
prompt: Trigger prompt
send: true
---
## User Input
\`\`\`text
$ARGUMENTS
\`\`\`
[Command instructions...]
```
### Standard Agent Skill Format
Location: `skills/<skill-name>/SKILL.md`
```yaml
---
name: skill-name
description: Complete description including what the skill does and when to use it.
---
# Skill Title
## When to Use
- Scenario 1
- Scenario 2
## Inputs
- Required input 1
- Optional input 2
## Workflow
1. Step 1
2. Step 2
...
## Outputs
- Output file 1
- Output file 2
```
## Conversion Workflow
1. **Read the source command** from `.claude/commands/`.
2. **Extract metadata**:
- `description` from YAML frontmatter.
- `handoffs` for related skills/next steps.
- `$ARGUMENTS` handling for inputs.
3. **Determine skill name**:
- Convert `command.name.md` → `command-name` (replace dots with hyphens).
- Use kebab-case for multi-word names.
4. **Create skill directory**: `skills/<skill-name>/`
5. **Transform content** to SKILL.md format:
- **Frontmatter**: Keep `name` and `description` only.
- **Enhance description**: Expand to include when to use the skill.
- **Convert `$ARGUMENTS`**: Document as Inputs section.
- **Structure workflow**: Extract steps into numbered Workflow section.
- **Add "When to Use"**: Derive from command context and description.
- **Add "Outputs"**: List generated files/artifacts.
- **Convert handoffs**: Add "Next Steps" section referencing related skills.
6. **Remove runtime-specific content**:
- Remove `## User Input` section with `$ARGUMENTS` block.
- Remove `handoffs` from frontmatter (move to prose).
- Remove `/command.name` references (use skill names instead).
7. **Validate skill structure**:
- Frontmatter has `name` and `description` only.
- Body has clear sections (When to Use, Inputs, Workflow, Outputs).
- No TODO placeholders remain.
- No runtime-specific variables like `$ARGUMENTS`.
8. **Report conversion result**:
- Source command path.
- Generated skill path.
- Key transformations applied.
- Manual review recommendations.
## Transformation Rules
| Claude Command | Agent Skill |
| ----------------------------- | --------------------------------------------- |
| `$ARGUMENTS` | Inputs section describing expected user input |
| `handoffs:` | Next Steps section with skill references |
| `/command.name` | `skill-name` (kebab-case) |
| `agent: foo.bar` | `foo-bar` skill reference |
| `description:` in frontmatter | `description:` expanded with triggers |
| Inline `## User Input` | Removed; documented in Inputs |
## Example Conversion
**Input**: `.claude/commands/speckit.specify.md`
```yaml
---
description: Create feature specification from natural language.
handoffs:
- label: Build Technical Plan
agent: speckit.plan
---
## User Input
\`\`\`text
$ARGUMENTS
\`\`\`
The text the user typed after `/speckit.specify`...
```
**Output**: `skills/speckit-specify/SKILL.md`
```yaml
---
name: speckit-specify
description: Create or update a feature specification from a natural language feature description.
---
# Spec Kit Specify Skill
## When to Use
- The user wants a new or updated feature spec from a natural language description.
## Inputs
- Feature description from the user.
- Repo context with `.specify/` scripts and templates.
If the description is missing or unclear, ask a targeted question before continuing.
## Workflow
...
## Outputs
- `specs/<feature>/spec.md`
- `specs/<feature>/checklists/requirements.md`
## Next Steps
After generating spec.md:
- **Plan** technical implementation with speckit-plan.
- **Clarify** specification requirements with speckit-clarify.
```
## Key Rules
- Preserve all workflow logic and instructions.
- Remove runtime-specific constructs (`$ARGUMENTS`, `handoffs`, `/slash-commands`).
- Expand terse descriptions to include usage triggers.
- Use imperative voice in workflow steps.
- Keep skills self-contained and portable.
- Don't add extraneous documentation files (README, CHANGELOG, etc.).
## Next Steps
After conversion:
- Review generated SKILL.md for completeness.
- Delete unused example files in `scripts/`, `references/`, `assets/`.
- Update AGENTS.md/CLAUDE.md skill inventory if applicable.
- Create symlinks for runtime integration if needed.
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.