agentleFS
pahlevikunpahlevikun/levistack/skills/agent-authoring/create-agent/SKILL.md

create-agent

Skill0 starsChanged 18 days agoMITView on GitHub

Create, audit or improve subagents (agents/*.md for Claude Code and Cursor). Use when asked to add or review a subagent, fix an agent description that never delegates, or choose its tools and model. Not for skills (use create-skill).

38 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use deploy-platform, setup-platform and 6 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • agno-agiSkill

    deploy-platform

    Deploy this AgentOS using its own provider instructions, configure JWT verification, and verify the public service. Use for first deployment, redeployment, or production configuration changes.

    Also in 5 projects that use this

  • agno-agiSkill

    setup-platform

    Set up this AgentOS from a fresh clone — confirm Docker, configure .env, boot the containers, prove the MCP endpoint live, connect the AgentOS UI, then build the user's first agent. Use when the user asks to set up the platform, get started, or bring this repo up on a new machine.

    Also in 5 projects that use this

  • ElasticSkill

    create-integration

    Use when creating a new Elastic integration package, scaffolding data streams, answering package layout or structure questions, or running the end-to-end integration build workflow. Covers package topology, scaffold commands, post-scaffold edits, and full orchestration of CEL/pipeline/test subagents.

    Also in 3 projects that use this

  • AnasX7Skill

    improve

    Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.

    Also in 5 projects that use this

  • SentrySkill

    create-pr

    Create pull requests following Sentry conventions. Use when opening PRs, writing PR descriptions, or preparing changes for review. Follows Sentry's code review guidelines.

    Also in 3 projects that use this

  • +3 more from agno-agi

The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 35 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Assume the model is smart: Add only what it lacks: your conventions, your commands, the traps.

    line 33
  2. Distinctive:

    One job per agent: If it needs "and", split it.

    line 34
  3. Distinctive:

    Test: ask for it by name ("use the X subagent to ..."), then give a task that should delegate on its own.

    line 66
  4. Very specific:

    Run node scripts/lint.mjs <path> on an agent file or a directory of agents.

    line 70
  5. Distinctive:

    No overlap with an existing agent, or the overlap was merged.

    line 88

“Common” is measured: kept by at least 6 in 10 of the 35 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Create subagents

A subagent is a Markdown file whose body is a system prompt. It runs in its own context, optionally with fewer tools or another model, and returns a summary.

Related skills in this group: create-skill (SKILL.md folders), create-rule, create-hook, create-command, convert-as-skill, and create-agents-md (AGENTS.md).

Principles

  1. The description is the router. The model decides to delegate from description alone. Write what it does, when to use it, and the words a user would say.
  2. Assume the model is smart. Add only what it lacks: your conventions, your commands, the traps. Cut explanations of common knowledge.
  3. One job per agent. If it needs "and", split it. If two overlap, merge them.
  4. Smallest authority. Grant the fewest tools and the smallest model that works. Read-only unless it must write.
  5. Keep the prompt short. About 80 lines. Link to rules and references instead of pasting them.
  6. Test by using it. An untested description is a guess.

Choose the right mechanism

NeedUse
Isolate noisy or parallel work, restrict tools, use a cheaper modelSubagent
A reusable procedure or knowledge, loaded when relevantSkill (create-skill)
Facts true for the whole repo, always in contextAGENTS.md (create-agents-md) or a rule (create-rule)
Must happen every time, not model-decidedHook (create-hook)
A saved prompt you type as /nameA command (create-command)

A skill can run as a subagent: in Claude Code set context: fork and agent: <type> (see create-skill).

What do you want to do?

  1. New subagent → New subagent
  2. Audit existing agents → Audit
  3. New or oversized skill → use create-skill

Infer the intent from the request; ask only if it is unclear. If the conversation already described a recurring task, derive the agent from it instead of asking again.

New subagent

  1. Check for overlap. List the existing agents (project, user, plugin). Extend or merge before creating. A large roster of vague agents makes delegation worse.
  2. Pick the location. Shared with the team: the project's agents/ (plugin) or .claude/agents/ / .cursor/agents/. Personal: ~/.claude/agents/ or ~/.cursor/agents/. Cursor also reads .claude/agents and .codex/agents, so one file can serve several tools. See subagents.md.
  3. Write the frontmatter from templates/subagent.md: name, a description that says when to call it, tools (or readonly), and model only if the work is mechanical.
  4. Write the body as a short system prompt: mission, the inputs the caller must pass, numbered steps, how to verify, the output format, an explicit "Do not" list. About 80 lines at most.
  5. Lint with node scripts/lint.mjs <file>.
  6. Test: ask for it by name ("use the X subagent to ..."), then give a task that should delegate on its own. Adjust the description until it triggers on the second and not on unrelated tasks.

Audit

  1. Run node scripts/lint.mjs <path> on an agent file or a directory of agents. The same linter also checks skill folders (create-skill uses it).
  2. Walk the checklist in audit.md for what a linter cannot judge (is the description specific, are the steps actionable, is the tool list minimal).
  3. Report a score and findings by priority, each with a concrete fix: Broken (will not load or trigger), Weak (loads but misroutes or wastes context), Polish.
  4. Apply only the fixes the user asked for. Preserve the author's structure and voice.

Related skills

  • create-skill: the job is a procedure the main agent runs, not a delegate.
  • create-command: the job is a saved prompt you type as /name.
  • create-hook: the job must run on an event, with no model decision.
  • create-rule: the guidance must apply on every task.
  • convert-as-skill: turn an existing agent into a skill.

Done when

  • name matches the filename; description states when to call it; the linter reports no errors.
  • Tools and model are the minimum that works.
  • It was exercised at least once on a real task, and the description triggered correctly.
  • No overlap with an existing agent, or the overlap was merged.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.