Create production-grade agent .md files aligned with the current Anthropic subagent contract.

MITAuto-check passedAgent Workflows

Install Agent Creator

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill agent-creator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace agent-creator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/agent-creator .claude/skills/agent-creator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agent-creator
GitHub stars
2.8k
Token cost
~4k tokens
SKILL.md length
1,656 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Create production-grade agent .md files aligned with the current Anthropic subagent contract.

  • Works in 6 steps: Understand Requirements → Plan the Agent → Write the Agent File → …
  • Building custom subagents
  • SKILL.md covers Overview, Prerequisites, Instructions and Validation Workflow, plus 4 more sections
  • Calls python3

What it does

Agent Creator is an agent skill from jeremylongshore/tons-of-skills-marketplace. Create production-grade agent .md files aligned with the current Anthropic subagent contract. 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.

Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/anthropic-agent-spec.md`). Compatibility notes: Designed for Claude Code

It sits in Agent Workflows, covering Subagents and Building AI agents. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Building custom subagents
  • Reviewing agent quality
  • Creating parallel agent architectures for orchestrator skills
  • With /agent-creator

Example prompts

  • “/agent-creator”
  • “create an agent”
  • “build a subagent”
  • “/agent-creator”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Glob, Grep, Bash(python:*), AskUserQuestion, Agent

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Understand Requirements
  2. Plan the Agent
  3. Write the Agent File
  4. Validate the Agent
  5. Test the Agent
  6. Report

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Glob
    • Grep
    • Bash(python:*)
    • AskUserQuestion
    • Agent

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Agent Creator loads about 4k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 124 tokens; SKILL.md has 1,656 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~124
When it runs · the whole SKILL.md, loaded when a task matches
~4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 1,656 words, ~3,995 tokens.

Download SKILL.mdSave it as .claude/skills/agent-creator/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
agent-creator
description
Create production-grade agent .md files aligned with the current Anthropic subagent contract. 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.
allowed-tools
Read, Write, Edit, Glob, Grep, Bash(python:*), AskUserQuestion, Agent
compatibility
Designed for Claude Code
argument-hint
<create|validate> [agent path or requirements]
version
5.23.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
agent-creation, validation, meta-tooling, subagents
model
inherit
effort
high

Agent Creator

Creates spec-compliant agent .md files following Anthropic's current documented subagent frontmatter contract. 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 distinguishes the 16 fields in Anthropic's public frontmatter table from runtime-recognized experimental options, then layers the stricter Intent Solutions required set on top. It 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). Skills use allowed-tools (allowlist) and, since schema 3.7.0, an optional kebab-case disallowed-tools denylist — a parallel field, not a unification. Agents also support effort, maxTurns, skills, memory, isolation, permissionMode, background, color, and initialPrompt — fields that don't exist for skills. Claude Code also recognizes a separately labeled runtime experimental object; do not present it as part of the public 16-field table. The agent body becomes the system prompt that drives the subagent — it does NOT receive the full Claude Code system prompt.

Field-naming warning: Agents use camelCase disallowedTools: (canonical sub-agents spec); skills use kebab-case disallowed-tools: (schema 3.7.0+). The validator rejects either mismatch — never copy-paste between agent and skill frontmatter without renaming.

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 (20-1536 chars under the IS contract; keep it concise for the selection UI)

Execution Context:

  • Plugin agent (plugins/*/agents/) or standalone (~/.claude/agents/)?
  • Will it run as the main --agent, or be spawned through the Agent tool?
  • May it delegate to nested subagents? If yes, include Agent; if no, omit or deny it.
  • Does it need to preload specific skills? (skills: [skill-name])

Behavioral Controls:

  • Model override? (sonnet, opus, haiku, fable, inherit, or a full Claude model ID)
  • 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:

SectionPurposeRequired?
# TitleAgent name as headingYes
## Role2-3 sentence domain description with boundariesYes
## InputsParameters the agent receives when spawnedYes (if spawned by orchestrator)
## ProcessStep-by-step methodology (numbered steps with ### headings)Yes
## Output FormatStructured output spec (JSON, markdown, or table)Yes
## GuidelinesDo/don't behavioral rulesYes
## When ActivatedTrigger conditions (when spawned or auto-detected)Recommended
## Communication StyleTone and formatting preferencesRecommended
## Success CriteriaWhat good vs poor output looks likeRecommended
## ExamplesConcrete interaction examplesFor 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. Use Write for a new definition and Edit for a targeted remediation of an existing definition; do not replace unrelated project content.

Frontmatter Rules (documented schema plus runtime extension):

See Anthropic Agent Spec for the full official reference.

Upstream-required fields:

yaml
name: {agent-name}         # Lowercase letters and hyphens, unique identifier
description: "{specialty}"  # When Claude should delegate to this subagent

For marketplace output, the IS overlay also emits tools, model, color, version, author, tags, disallowedTools, skills, and background. Standalone agents additionally emit hooks, mcpServers, and permissionMode; omit those three from plugin agents. The remaining tuning fields stay optional until the requested behavior needs them.

Marketplace fields and optional tuning controls:

yaml
tools: "Read, Glob, Grep"  # Allowlist — inherits all tools if omitted
disallowedTools: [Write]   # IS denylist form — removed from inherited/specified list
model: sonnet              # sonnet|haiku|opus|fable|inherit|full Claude model ID
color: blue                # Display: red|blue|green|yellow|purple|orange|pink|cyan
version: 1.0.0
author: "Name <email@example.com>"
tags: [specialty, workflow]
effort: medium             # low|medium|high|xhigh|max (availability depends on model)
maxTurns: 15               # Max agentic turns before stopping
skills: [skill-name]       # Skills to preload (unlisted skills remain invocable)
memory: project            # user|project|local — persistent cross-session
background: false          # Always run as background task
isolation: worktree        # Run in temporary git worktree
initialPrompt: "..."       # Auto-submitted first turn (--agent mode only)
permissionMode: default    # Also accepts manual as a default alias; ignored in plugins
hooks: {}                  # Standalone only, NOT plugin agents
mcpServers: []             # Standalone only; names or inline definitions
experimental:              # Claude Code v2.1.248+; optional
  cacheTtl: 5m             # 5m|1h

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
  • Naming: always emit camelCase disallowedTools on agents. Skills spell their denylist kebab-case (disallowed-tools, schema 3.7.0+) — the validator rejects camelCase on skills and kebab-case on agents, so never copy-paste between the two without renaming

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
  • disallowed-tools (kebab-case) — skill-only spelling (schema 3.7.0+); agents use camelCase 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.

Show full SKILL.md (649 more words)Show less
Step 4: Validate the Agent

Run validation against the documented Anthropic schema and the runtime extension allowlist:

Manual checklist:

CheckRule
name present1-64 chars, kebab-case
description present20-1536 chars under the IS contract; concise and selection-specific
No invalid fieldsNone of: capabilities, expertise_level, activation_priority, type, category
No skill-only fieldsNo allowed-tools, no kebab-case disallowed-tools (agents use tools / camelCase disallowedTools)
Plugin restrictionsNo hooks/mcpServers/permissionMode if plugin agent
Body has Role sectionClear domain + boundaries
Body has Process sectionNumbered steps
Body has Output FormatConcrete schema example
Body has GuidelinesDo/don't rules
Body under 300 linesOffload to references if longer (prevents context bloat)

Automated validation:

bash
python3 ${CLAUDE_SKILL_DIR}/../skill-creator/scripts/validate-skill.py --agents-only {plugin-dir}/
Step 5: Test the Agent

Test the agent by spawning it via the Agent tool:

  1. Write a test prompt that exercises the agent's core capability
  2. Spawn the agent with that prompt
  3. Check: Does the output match the declared Output Format?
  4. Check: Does the agent stay within its declared Role boundaries?
  5. Check: Does it follow the Process steps?
  6. Iterate on the body content if the agent strays
Step 6: Report

Provide a summary:

  • Agent name and file path
  • Documented frontmatter fields used, plus any runtime extension and IS overlay fields used
  • Body line count
  • Sections present
  • Validation result (pass/fail with specific issues)
  • Test result summary

Validation Workflow

When the user wants to validate an existing agent:

  1. Locate the agent .md file
  2. Parse YAML frontmatter
  3. Check against the documented Anthropic schema and runtime extension allowlist:
    • name present and valid (1-64 chars, kebab-case)?
    • description present and valid (20-1536 chars; concise and selection-specific)?
    • Any invalid fields? (capabilities, expertise_level, activation_priority, etc.)
    • Any skill-only fields? (allowed-tools, kebab-case disallowed-tools)
    • Plugin restrictions respected?
  4. Check body content:
    • Has ## Role section?
    • Has ## Process section with numbered steps?
    • Has ## Output Format with concrete example?
    • Has ## Guidelines?
    • Under 300 lines? (agent body limit)
  5. Report findings with severity (ERROR/WARNING/INFO)
  6. Suggest specific fixes for each issue

Output

  • Create mode: A complete agent .md file with valid frontmatter and substantive body, plus a creation report with validation status.
  • Validate mode: A compliance report listing errors, warnings, and info items with specific fix recommendations for each.

Examples

Subagent for Orchestrator Skill

Input: "Create a risk assessment agent that scores contract clauses"

Output: agents/risk-assessor.md with frontmatter:

yaml
name: risk-assessor
description: "Score contract clauses for legal and financial risk on a 1-10 scale"
model: sonnet
effort: high
maxTurns: 10

Body sections: Role (risk scoring specialist, does NOT make recommendations), Inputs (contract_text, contract_type, output_path), Process (4 steps: read, categorize, score, aggregate), Output Format (JSON with clause scores and risk matrix), Guidelines (be specific, cite clause text, use 4-factor scoring methodology).

Standalone User-Facing Agent

Input: "Create a code review agent"

Output: ~/.claude/agents/code-reviewer.md with frontmatter:

yaml
name: code-reviewer
description: "Review code for bugs, performance issues, and security vulnerabilities"
effort: high

Body sections: Role (code quality specialist), Process (read code, check patterns, identify issues, suggest fixes), Output Format (markdown with severity-rated findings), Guidelines (cite line numbers, explain why not just what), Communication Style (direct, educational, actionable).

Error Handling

ErrorCauseResolution
allowed-tools in agentUsed skill-only fieldReplace with tools (allowlist) or disallowedTools (denylist), or remove
disallowed-tools (kebab-case) in agentCopy-pasted from skill frontmatterRename to camelCase disallowedTools — the validator rejects the kebab-case spelling on agents
capabilities fieldCommon mistake — looks valid but isn't in Anthropic specRemove field entirely
expertise_level fieldInvented field from community templatesRemove — express expertise in body content
Description > 1536 charsExceeds the IS disclosure-marker capShorten below 1536 chars and keep it concise
Description < 20 charsBelow minimumExpand to describe agent's specific specialty
permissionMode in plugin agentStandalone-only field used in plugin contextRemove — only valid in ~/.claude/agents/
hooks in plugin agentPlugin agents can't have hooksMove to plugin-level hooks/hooks.json
Body has no Process sectionAgent lacks step-by-step methodologyAdd numbered steps under ## Process
Body over 300 linesToo long for agent contextExtract reference material to companion skill

Resources

  • Anthropic Agent Spec — documented 16-field table plus the separately labeled runtime extension
  • Agent template — Skeleton with placeholders
  • Frontmatter spec — Field reference (internal)
  • Source of truth — Canonical spec
  • Validation rules — Agent validation section

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/agent-creator of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/anthropic-agent-spec.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Agent Creator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agent Creator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agent Creator this skilljeremylongshore/tons-of-skills-marketplace2.8k—~4kAutomated safety check: PassMIT
Create Agentvectorize-io/hindsight48k—~1.1kAutomated safety check: PassMIT
Deep Agentslangchain-ai/docs426—~1.1kAutomated safety check: PassMIT
Create AgentApocrathia/home-assistant-config179—~1.1kAutomated safety check: PassNone
Agent Creatorsickn33/agentic-awesome-skills47k1 repos~2.7kAutomated safety check: PassMIT
Building Agentsaiskillstore/marketplace433—~4.2kAutomated safety check: NotesNone

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Questions about Agent Creator

What does Agent Creator do?

Create production-grade agent .md files aligned with the current Anthropic subagent contract. Agent Creator is an agent skill from jeremylongshore/tons-of-skills-marketplace.md files aligned with the current Anthropic subagent contract.

When should I use Agent Creator?

Agent Creator fits situations like: building custom subagents; reviewing agent quality; creating parallel agent architectures for orchestrator skills; with /agent-creator.

How do I install Agent Creator in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill agent-creator -a claude-code`. Or copy the skill folder (skills/.curated/agent-creator in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/agent-creator in your project. Claude Code loads it when a task matches its description.

How do I install Agent Creator in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill agent-creator -a codex`. Or copy the skill folder (skills/.curated/agent-creator in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/agent-creator in your project. Codex loads it when a task matches its description.

Can I use Agent Creator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill agent-creator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-creator, .gemini/skills/agent-creator, .github/skills/agent-creator and .opencode/skills/agent-creator in your project.

What does Agent Creator need to run?

Going by SKILL.md and its folder, Agent Creator needs the command-line tools its instructions call (python3). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Glob, Grep, Bash(python:*), AskUserQuestion, Agent. Compatibility (from SKILL.md): Designed for Claude Code.

Does Agent Creator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Agent Creator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agent Creator use?

Agent Creator is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Creator use?

About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Agent Creator?

Skills that share tags, products or a category with Agent Creator: Create Agent (vectorize-io/hindsight, 48k stars), Deep Agents (langchain-ai/docs, 426 stars), Create Agent (Apocrathia/home-assistant-config, 179 stars) and Agent Creator (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Creator?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.