rent — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited rent (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Auto-activate when the user wants to hire a person, post a job, or delegate a task that needs a human.
/rent — Browse + print command menu
/rent scan — AI-scored bounties (Grok, 12hr cache)
/rent scan force — Bypass cache, fresh scoring now
/rent scan new — Only unseen bounties
/rent post <desc> — Post a new bounty (first sentence = title)
/rent saved — View saved bounties
/rent skills — List available human skills
/rent status — Connection checkDirect: /rent search <skill> → /rent human <id> → /rent talk <id> : msg → negotiate → book Bounty: /rent post desc → humans apply → /rent applications <id> → /rent accept <app_id>
Script: python3 .claude/skills/rent/scripts/bounty_hunter.py Cache: logs/bounties_cache.json (12hr TTL, Grok-3-mini-fast scoring 0–100) After running: read cache file and display scored results to user.
Bounties: 5/day | Conversations: 50/day | Messages: 30/hr | API keys: 3 max
python hire_team.py "Task description"
python hire_team.py talk <human_id> "Message"
python hire_team.py bounty "Title" --description "..." --price 100 --hours 2Note: hire_team.py is an optional external CLI. Primary interface is MCP via /rent commands.
Payment via Stripe Connect escrow on RentAHuman.ai.
→ Full command tree + MCP tool map: .claude/commands/rent.md
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.