agent-creator
Create production-grade agent .md files aligned with the Anthropic 2026 spec (16-field schema). Also validates existing agents against the marketplace compliance rules. Use when building custom subagents, reviewing agent quality, or creating parallel agent architectures for orchestrator skills. Trigger with "/agent-creator", "create an agent", "build a subagent", or "validate my agent". Make sure to use this skill whenever creating agents/*.md files for plugins or standalone use.
What this skill does
# Agent Creator
Creates spec-compliant agent .md files following the Anthropic 2026 16-field schema. Supports
both creation of new agents and validation of existing ones.
## Overview
Agent Creator fills the gap between ad-hoc agent files and production-grade agents that pass
marketplace validation. It enforces the Anthropic agent schema (14 valid fields), prevents
common mistakes (using `allowed-tools` instead of `disallowedTools`, adding invalid fields like
`capabilities` or `expertise_level`), and produces agents with substantive body content that
actually guides Claude's behavior.
Key difference from skill-creator: **agents support both `tools` (allowlist) AND `disallowedTools`
(denylist)**, while skills only use `allowed-tools` (allowlist). Agents also support `effort`,
`maxTurns`, `skills`, `memory`, `isolation`, `permissionMode`, `background`, `color`, and
`initialPrompt` — fields that don't exist for skills. The agent body becomes the **system prompt**
that drives the subagent — it does NOT receive the full Claude Code system prompt.
## Prerequisites
- Claude Code CLI with agent support
- Target directory writable (`agents/` within a plugin or `~/.claude/agents/` for standalone)
- Familiarity with what the agent should specialize in
## Instructions
### Mode Detection
Determine user intent from their prompt:
- **Create mode**: "create an agent", "build a subagent", "new agent" -> Step 1
- **Validate mode**: "validate agent", "check agent", "grade agent" -> Validation Workflow
### Step 1: Understand Requirements
Ask the user with AskUserQuestion:
**Agent Identity:**
- Name (kebab-case, 1-64 chars, e.g., `risk-assessor`, `clause-analyzer`)
- Specialty description (20-200 chars — shown in agent selection UI)
**Execution Context:**
- Plugin agent (`plugins/*/agents/`) or standalone (`~/.claude/agents/`)?
- Will it be spawned by an orchestrator skill via `Task` tool?
- Does it need to preload specific skills? (`skills: [skill-name]`)
**Behavioral Controls:**
- Model override? (`sonnet` for speed, `opus` for quality, `inherit` for default)
- Reasoning effort? (`low` for simple, `medium` default, `high` for complex analysis)
- Max iterations? (`maxTurns` — how many tool-use loops before stopping)
- Tools to deny? (`disallowedTools` — denylist approach, opposite of skills)
**Plugin Restrictions (if plugin agent):**
- `hooks` — NOT supported in plugin agents (use plugin-level hooks)
- `mcpServers` — NOT supported in plugin agents
- `permissionMode` — standalone only, NOT plugin agents
### Step 2: Plan the Agent
Before writing, determine:
**Agent Role Clarity:**
The agent body must make three things unambiguous:
1. **What it IS responsible for** — its specific domain/methodology
2. **What it is NOT responsible for** — boundaries with other agents
3. **How it communicates results** — output format and structure
**Body Structure Pattern:**
All production agents should follow this body structure:
| Section | Purpose | Required? |
|---------|---------|-----------|
| `# Title` | Agent name as heading | Yes |
| `## Role` | 2-3 sentence domain description with boundaries | Yes |
| `## Inputs` | Parameters the agent receives when spawned | Yes (if spawned by orchestrator) |
| `## Process` | Step-by-step methodology (numbered steps with ### headings) | Yes |
| `## Output Format` | Structured output spec (JSON, markdown, or table) | Yes |
| `## Guidelines` | Do/don't behavioral rules | Yes |
| `## When Activated` | Trigger conditions (when spawned or auto-detected) | Recommended |
| `## Communication Style` | Tone and formatting preferences | Recommended |
| `## Success Criteria` | What good vs poor output looks like | Recommended |
| `## Examples` | Concrete interaction examples | For complex agents |
**Output Structure Decision:**
- If the agent feeds into an orchestrator: use **JSON output** (machine-parseable)
- If the agent is user-facing: use **markdown output** (human-readable)
- If the agent produces both: JSON primary with markdown summary
### Step 3: Write the Agent File
Generate the agent .md using the template from
`${CLAUDE_SKILL_DIR}/../skill-creator/templates/agent-template.md`.
**Frontmatter Rules (Anthropic 16-field schema):**
See [Anthropic Agent Spec](references/anthropic-agent-spec.md) for the full official reference.
Required fields:
```yaml
name: {agent-name} # Lowercase letters and hyphens, unique identifier
description: "{specialty}" # When Claude should delegate to this subagent
```
Optional fields (include only what's needed):
```yaml
tools: "Read, Glob, Grep" # Allowlist — inherits all tools if omitted
disallowedTools: "Write" # Denylist — removed from inherited/specified list
model: sonnet # sonnet|haiku|opus|inherit|full model ID
effort: medium # low|medium|high|max (max = Opus 4.6 only)
maxTurns: 15 # Max agentic turns before stopping
skills: [skill-name] # Skills to inject at startup (full content loaded)
memory: project # user|project|local — persistent cross-session
background: false # Always run as background task
isolation: worktree # Run in temporary git worktree
color: blue # Display: red|blue|green|yellow|purple|orange|pink|cyan
initialPrompt: "..." # Auto-submitted first turn (--agent mode only)
permissionMode: default # Standalone only, NOT plugin agents
hooks: {} # Standalone only, NOT plugin agents
mcpServers: {} # Standalone only, NOT plugin agents
```
**Tool access:**
- `tools` = allowlist (like skills' `allowed-tools`)
- `disallowedTools` = denylist (remove specific tools)
- If both set: disallowed applied first, then tools resolved
- If neither set: inherits all tools from parent conversation
**Invalid fields (ERROR — never use these):**
- `capabilities` — looks valid but flagged by validator
- `expertise_level` — invented, not in Anthropic spec
- `activation_priority` — invented, not in Anthropic spec
- `activation_triggers`, `type`, `category` — not in spec
- `allowed-tools` — that's the skill-only syntax; agents use `tools` or `disallowedTools`
**Body Content Guidelines:**
1. **Role section must set boundaries.** Don't just say what the agent does — say what it
does NOT do. Example: "You analyze contract clauses for risk. You do NOT provide legal
advice or make recommendations — that is the recommendations agent's responsibility."
2. **Process steps must be concrete.** Each step should tell Claude exactly what to do,
not vaguely gesture at an activity. Bad: "Analyze the document." Good: "Read the full
contract. For each clause, extract: (a) the exact text, (b) the clause category from
the taxonomy below, (c) a plain English summary in one sentence."
3. **Output format must be machine-parseable if feeding an orchestrator.** Use JSON with
a concrete schema example. Include field descriptions so Claude knows what each field means.
4. **Guidelines should include both DO and DON'T rules.** Example:
- DO: "Be specific — quote exact clause text, don't paraphrase"
- DON'T: "Don't make legal recommendations — only identify and score risks"
5. **Keep under 300 lines** (agent body limit — prevents context bloat in subagent window).
If the agent needs extensive reference material, create a companion skill with
`references/` directory and preload it via the `skills` field.
### Step 4: Validate the Agent
Run validation against the Anthropic 16-field schema:
**Manual checklist:**
| Check | Rule |
|-------|------|
| `name` present | 1-64 chars, kebab-case |
| `description` present | 20-200 chars |
| No invalid fields | None of: capabilities, expertise_level, activation_priority, type, category |
| No skill-only fields | No `allowed-tools` (use `disallowedTools` instead) |
| Plugin restrictions | No hooks/mcpServers/permissionMode if plugin agent |
| Body has Role section | Clear domain + boundaries |
| Body has ProceRelated 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.