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 magnus919/agent-skills --skill production-excellencegit clone --depth 1 https://github.com/magnus919/agent-skillsWrote 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/magnus919/agent-skills/production-excellence)<a href="https://agentmods.dev/skills/magnus919/agent-skills/production-excellence"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/production-excellence/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/magnus919/agent-skills/production-excellence"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/production-excellence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.02287 |
| Opus 5 | $0.00028 | $0.01144 |
| Sonnet 5 | $0.00011 | $0.00457 |
| Haiku 4.5 | $0.00006 | $0.00229 |
Grade A, and why
production-excellence 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 9d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Production Excellence
A thin composition bundle that assembles cross-domain production evidence into a defensible launch or operational decision. It owns the acceptance and handoff layer — the gate model that reads evidence from specialist skills and produces go / no-go / defer / exception / escalation outcomes with accountable owners. It does not own any specialist's runbook.
When to load this
Load when:
- A service or change is approaching a launch decision and evidence from multiple production domains must be assembled.
- You need a structured gate model (go/no-go/defer/exception/escalation) with conditions, evidence, and accountable owners.
- Cross-domain evidence (readiness, migration, recovery, capacity/cost, incident history) must be combined into one operational handoff record.
- A launch or change needs a post-launch learning path routed to incident-learning and product-lifecycle-learning.
- You are coordinating a production change across SRE, release, platform, security, data, and QA specialists and need a single acceptance contract.
When not to use
Do not load this bundle for:
- Incident command or SLO operations — those are owned by site-reliability-engineering.
- Release-pipeline mechanics, versioning, or deployment strategies — those are owned by release-engineering.
- Platform architecture or internal-developer-platform design — those are owned by platform-engineering.
- Threat modeling, security review procedure, or vulnerability assessment — those are owned by secure-software-engineering.
- Data-pipeline design, ETL, or storage architecture — those are owned by data-engineering.
- Test-strategy design, regression-suite management, or test-automation framework design — those are owned by qa-methodology.
- A generic checklist detached from service ownership, risk, evidence, and verification — every gate in this bundle requires a named service owner, assessed risk, verified evidence, and a declaration of the verification boundary. A bare checklist is never a valid outcome.
What ships with it
8 files 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.
- 9d ago First seen · 175 lines · 56 tokens per session scan A e7be1f180291
production-excellence is a skill published in the GitHub repository magnus919/agent-skills (76 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 2,287 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 2026-09-03.
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