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 Nmor/the-claude-council --skill six-sigmagit clone --depth 1 https://github.com/Nmor/the-claude-councilWrote 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/nmor/the-claude-council/six-sigma)<a href="https://agentmods.dev/skills/nmor/the-claude-council/six-sigma"><img src="https://agentmods.dev/badge/skills/nmor/the-claude-council/six-sigma/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/nmor/the-claude-council/six-sigma"><img src="https://agentmods.dev/badge/skills/nmor/the-claude-council/six-sigma.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 | $0.00080 | $0.05482 |
| Opus 5 | $0.00040 | $0.02741 |
| Sonnet 5 | $0.00016 | $0.01096 |
| Haiku 4.5 | $0.00008 | $0.00548 |
Grade A, and why
six-sigma 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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 · 565 lines · 80 tokens per session scan A 5eb4a63cf4b9
six-sigma is a skill published in the GitHub repository Nmor/the-claude-council (9 stars, last pushed 5d ago), with no licence file. It adds 80 tokens to every session and 5,482 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 2026-09-03.
Other skills, from other repositories
code-review
Systematic code review for bugs, security, style, and performance.
refactoring-workflow
Improve the structure of existing code without changing its behaviour, in small verified steps under a green test suite. Use when the user asks to refactor, clean up, restructure or simplify code, wants to reduce duplication or coupling, is preparing a codebase for a feature it cannot currently accommodate, or when…
refactor-agent
Safe, systematic code refactoring — extract functions, reduce complexity, eliminate duplication, improve naming. Use when improving code structure without changing behavior.
review-prod-ready
Use when comprehensive production-readiness code review is needed after implementation — dispatches up to 7 specialized parallel reviewers covering tests, plan completeness, architecture, complexity, DRY violations, suppressed warnings, and production readiness.
github-code-review
Comprehensive GitHub code review with AI-powered swarm coordination.
Pair Programming
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with…