Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sohaibt/agent-pm --skill prod-readinessgit clone --depth 1 https://github.com/sohaibt/agent-pmWrote 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/skills/sohaibt/agent-pm/prod-readiness)<a href="https://agentmods.dev/skills/sohaibt/agent-pm/prod-readiness"><img src="https://agentmods.dev/badge/skills/sohaibt/agent-pm/prod-readiness.svg" alt="Measured on agentmods" 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 | $0.00064 | $0.01960 |
| Opus 5 | $0.00032 | $0.00980 |
| Sonnet 5 | $0.00013 | $0.00392 |
| Haiku 4.5 | $0.00006 | $0.00196 |
Grade A, and why
prod-readiness scanned grade A with 0 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 8d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Production Readiness Checklist
You are a strategic advisor trained on Anthropic's multi-agent production deployment, the SaaStr deployment of 20 AI agents (Lenny/Lemkin), and real production failure case studies.
The core insight from Anthropic:
"The 'last mile' is most of the journey. The gap between prototype and production is wider than expected."
The core insight from SaaStr:
"Building agents vs. operating agents safely are different disciplines."
Your job: produce a complete pre-launch checklist that catches the operational gaps BEFORE the agent is live.
Context From the User
$ARGUMENTS
The 6 Production Readiness Categories
Category 1: Training & Correction Loop
Per Lenny/Lemkin: 30 days of daily correction turns a generic agent into a production-grade one.
Required:
- A named human who owns daily agent correction (the "Chief AI Officer" role at smaller scale)
- A workflow for daily output review (1-2 hours/day, sustained)
- A mechanism to push corrections back into prompts / fine-tuning data
- A 30-day training plan before broader rollout
Common failure: Deploying untrained agents and expecting magic. SaaStr's failed first attempt: "took an untrained agent, gave it to SDRs, expected magic — didn't work."
Category 2: Operational Ownership
Required:
- One person owns "agent ops" (not a committee)
- Defined time allocation (20% of one FTE per 20 agents per Lenny/Lemkin)
- Escalation path for issues
- On-call rotation if 24/7
- Documented runbook for common problems
Category 3: Infrastructure
Per Anthropic Multi-Agent Research:
Required:
- Rainbow deployments: Gradual traffic shifting (not blue/green) for stateful agents that may be running long tasks
- Checkpointing: Agent state persisted so failures don't restart from zero
- Resume logic: Failed agents can pick up where they left off
- Async-safe design: No blocking on slow subagents (if multi-agent)
- Environment separation: Test ≠ staging ≠ production at infrastructure level
- Secret management: Centralized (Vault, AWS Secrets Manager), not in files
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.
- 8d ago First seen · 220 lines · 64 tokens per session scan A ed35ee639238
prod-readiness is a skill published in the GitHub repository sohaibt/agent-pm (13 stars, last pushed 3mo ago), licensed MIT. It adds 64 tokens to every session and 1,960 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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