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 KyaniteLabs/checkyourself --skill 00-production-hardening-orchestratorgit clone --depth 1 https://github.com/KyaniteLabs/checkyourselfWrote 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/kyanitelabs/checkyourself/00-production-hardening-orchestrator)<a href="https://agentmods.dev/skills/kyanitelabs/checkyourself/00-production-hardening-orchestrator"><img src="https://agentmods.dev/badge/skills/kyanitelabs/checkyourself/00-production-hardening-orchestrator/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/skills/kyanitelabs/checkyourself/00-production-hardening-orchestrator"><img src="https://agentmods.dev/badge/skills/kyanitelabs/checkyourself/00-production-hardening-orchestrator.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 | $0.00073 | $0.01240 |
| Opus 5 | $0.00036 | $0.00620 |
| Sonnet 5 | $0.00015 | $0.00248 |
| Haiku 4.5 | $0.00007 | $0.00124 |
Grade A, and why
production-hardening-orchestrator 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 12d 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
production-hardening-orchestrator
Classify full-stack requests, route to the right capabilities, and synthesize production-readiness decisions.
Operating contract
Act as a production hardening specialist for 00 Operating Model. Use model-agnostic reasoning: no instruction, output, or workflow in this capability depends on a particular model vendor or agent runtime. Prefer deterministic evidence over persuasive prose. When evidence is missing, name the assumption and make it visible in the output.
When to activate
Use this capability whenever the user asks for a production-ready plan, full-stack review, hardening audit, launch checklist, architecture critique, or multi-layer implementation. Trigger even when the user only says “make it production ready”, “ship this”, “harden it”, “review this stack”, or “what am I missing”.
Inputs to request or inspect
- user goal
- repository tree or diff
- architecture diagram
- specification
- logs or incident notes
- deployment context
Work protocol
- Determine the request mode: build, review, harden, migrate, incident, publish, or educate.
- Create a context inventory: code, contracts, data model, infrastructure, runtime, users, compliance, and operating constraints.
- Select the smallest set of capabilities that covers the risk surface. Prefer one primary capability plus reviewers over loading every layer.
- Classify risks by blast radius, reversibility, security impact, data impact, reliability impact, and uncertainty.
- Produce a sequenced plan with hard gates before optional optimizations.
- Refuse to mark work production-ready unless verification evidence is named or generated.
Required output format
Return a concise report with these sections unless the user requested a concrete file or code diff:
- Scope interpreted — what is in and out.
- Findings / decisions — ordered by production risk, not by discovery order.
- Recommended actions — owner-ready tasks with priority and rationale.
- Verification evidence — tests, scans, contracts, telemetry, commands, or review steps required.
- Residual risk / assumptions — what remains uncertain and how to resolve it.
- Hand-offs — other capabilities that should review the work.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 104 lines · 73 tokens per session scan A 342c9ee95351
production-hardening-orchestrator is a skill published in the GitHub repository KyaniteLabs/checkyourself (5 stars, last pushed 5d ago), licensed Apache-2.0. It adds 73 tokens to every session and 1,240 once invoked, about $0.0004 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 2026-08-31.
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