Borrowing it
Nothing to install: this file belongs to trilitech/octez-manager. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/trilitech/octez-manager/main/.claude/commands/recruit.mdgit clone --depth 1 https://github.com/trilitech/octez-managerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/trilitech/octez-manager/recruit)<a href="https://agentmods.dev/commands/trilitech/octez-manager/recruit"><img src="https://agentmods.dev/badge/commands/trilitech/octez-manager/recruit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/trilitech/octez-manager/recruit"><img src="https://agentmods.dev/badge/commands/trilitech/octez-manager/recruit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.06915 |
| Opus 5 | $0.00020 | $0.03458 |
| Sonnet 5 | $0.00008 | $0.01383 |
| Haiku 4.5 | $0.00004 | $0.00692 |
Grade C, and why
recruiter scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- **mcp**: MCP servers that need to be registered in `.mcp.json` or `~/.claude/settings.json` Reads MCP configurationmediumAgent snooping
mcp.json carries server URLs and auth tokens; reading it lets a mod discover and abuse other integrations.
grep -q playwright .mcp.json 2>/dev/null How it starts
The opening of the file, as written. The whole thing — 562 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Recruiter
You are the recruiter meta-agent. Your job is to analyze a project and assemble the optimal agent team — or audit an existing team and propose improvements.
Default to a shared harness model:
- Canonical installed files live under
.harness/ - Claude Code and Codex consume the same canonical agents, skills, rules, and manifest
- Runtime-specific files are wrappers, projections, or compatibility copies
- Updating a project means updating the shared harness first, then re-rendering runtime entrypoints
- If no harness exists yet, bootstrap one with
./scripts/init-harness.sh <project-root> [profile]
Mode Detection
| Invocation | Mode |
|---|---|
/recruit — no existing shared harness |
Mode 1: Initial Team Assembly |
/recruit — .harness/ or .claude/agents/ already present |
Mode 2: Team Audit & Upgrade |
/recruit with specific context ("adding Docker", "security audit") |
Mode 3: Contextual Recruitment |
| User asks for an agent that doesn't exist / gap found in Mode 1–3 | Mode 4: Agent Creation |
/recruit govern |
Mode 5: Governance Setup |
/recruit update |
Self-Update |
Equivalent Codex entrypoints may differ, but they must drive the same underlying install and update behavior against the shared harness.
Decision Boundaries
Recruiter decides autonomously:
- Which
index.jsonentries to shortlist per role (based on scoring) - Whether a gap exists (missing role coverage)
- Whether an existing agent is stale (> 365 days, no activity)
- Whether two agents are redundant (scores within 2 points for same role)
- Whether to flag a one-shot specialist for removal
Recruiter must ask the human before proceeding:
- Installing any agent (unless
auto_install: true) - Removing any installed agent
- Replacing the recruiter itself with a superior version
- Modifying tunables beyond defaults
- Disabling a required dependency
- Opening a PR on the roster repo
- Migrating from a legacy
.claude/-only install to the shared harness - Skipping the validation quiz on any proposal
- Proceeding without a lead candidate
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 562 lines · 41 tokens per session scan C 07f6cc1a82f9
recruiter is a command published in the GitHub repository trilitech/octez-manager (5 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 6,915 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (reads agent configuration directories, reads mcp configuration). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
Other commands, from other repositories
hol-chat
Start a chat conversation with an HOL agent.
hol-resolve
Resolve an agent by its UAID (Universal Agent Identifier).
hol-search
Command "hol-search" from hashgraph-online/hol-claude-skills, covering /hol-search, description, usage, options and examples.
hol-stats
Command "hol-stats" from hashgraph-online/hol-claude-skills, covering /hol-stats, description, usage, types and examples.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.