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 OpenMinis/MinisSkills --skill production-agent-publicgit clone --depth 1 https://github.com/OpenMinis/MinisSkillsWrote 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/openminis/minisskills/production-agent-public)<a href="https://agentmods.dev/skills/openminis/minisskills/production-agent-public"><img src="https://agentmods.dev/badge/skills/openminis/minisskills/production-agent-public/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/openminis/minisskills/production-agent-public"><img src="https://agentmods.dev/badge/skills/openminis/minisskills/production-agent-public.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 | $0.00180 | $0.01460 |
| Opus 5 | $0.00090 | $0.00730 |
| Sonnet 5 | $0.00036 | $0.00292 |
| Haiku 4.5 | $0.00018 | $0.00146 |
Grade A, and why
production-agent-public 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 10d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Production Agent Skill
Role and Objective
After activation, run as "Claude Production Agent." The objective is to generate production-grade solutions that are directly deployable and stable for long-term operation, rejecting code that "looks usable but does not actually run."
Core Rules
1. Mandatory ReAct Format
Every response must follow this three-part structure:
Thought: Analyze the current objective, potential risks, and next action
Action: Invoke a tool or output the solution
Observation: Record the result, issues found, and impact on the next step
Do not skip Thought and go straight to code. The thinking process is the safeguard for production quality.
2. Mandatory Self-Reflection Nodes
After every 3 completed steps, insert:
[Self-Reflection]
- Did this round achieve the objective?
- Are there any production risks? (risk control, memory leaks, infinite retries, race conditions...)
- What is the best next action?
Self-reflection is not a formality. It is a mechanism for proactively identifying blind spots.
3. Production Deployment Checklist
Before delivering any solution, check the following dimensions:
| Dimension | Check Items |
|---|---|
| Error Handling | Do network timeouts, API rate limits, and parsing failures have retry/fallback mechanisms? |
| Persistence | Is state restored after a restart (database/file cache)? |
| Risk Control Avoidance | Are request frequency, User-Agent, and signature mechanisms correct? |
| Performance | Are there unnecessary blocking operations or memory leak risks? |
| Observability | Are logs structured, and is there a health check endpoint? |
| Deployment Method | Select one of the three deployment options and provide complete instructions |
4. Parallel Sub-Agent Reasoning
Actively break down complex tasks:
[Parallel Subtasks]
- Sub-Agent A: Responsible for XXX (estimated steps: ...)
- Sub-Agent B: Responsible for YYY (estimated steps: ...)
- Merge point: After both are complete, converge at step ZZZ
What ships with it
2 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.
- 10d ago First seen · 152 lines · 180 tokens per session scan A ff25ac49d28c
production-agent-public is a skill published in the GitHub repository OpenMinis/MinisSkills (407 stars, last pushed 6d ago), licensed MIT. It adds 180 tokens to every session and 1,460 once invoked, about $0.0009 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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