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 agentmods add skills/chf3198/copilot-governance/github-ruleset-architecturenpx skills add chf3198/copilot-governance --skill github-ruleset-architecturegit clone --depth 1 https://github.com/chf3198/copilot-governanceWrote 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/chf3198/copilot-governance/github-ruleset-architecture)<a href="https://agentmods.dev/skills/chf3198/copilot-governance/github-ruleset-architecture"><img src="https://agentmods.dev/badge/skills/chf3198/copilot-governance/github-ruleset-architecture.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 | $0.00031 | $0.00472 |
| Opus 5 | $0.00015 | $0.00236 |
| Sonnet 5 | $0.00006 | $0.00094 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
github-ruleset-architecture 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 3d 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.
What it actually says
GitHub Ruleset Architecture
Purpose
Create a deterministic, auditable protection model using GitHub rulesets as primary governance controls.
Scope
- Branch/tag rulesets
- Push rulesets where supported
- Ruleset layering with existing branch protection
- Bypass actor minimization
- Merge queue compatibility checks
Hard constraints
- No destructive migration in one pass.
- Preserve current enforcement unless explicitly approved.
- Prefer staged rollout:
Disabled-> validate ->Active. - Always report bypass principals explicitly.
Core checks
- Ruleset target patterns (fnmatch) are precise and non-overlapping where possible.
- Layered rules produce intended effective policy (most restrictive wins).
- Bypass is least-privilege (role/team/app, justified).
- Merge queue requirements align with rules/protections.
- Required checks include
merge_groupreadiness where merge queue is used.
Output contract
RULESET_ARCHITECTURE_REPORT
mode: <audit|design|migrate|verify>
scope: <repo|org>
policy_profile: <strict|standard|light>
current_state:
- rulesets_found: <count>
- branch_protection_found: <yes|no>
- merge_queue_required: <yes|no>
findings:
- id: R1
result: <pass|fail|partial>
observation: <what exists>
risk: <low|medium|high>
proposed_changes:
1) change: <specific rule/ruleset>
rationale: <why>
rollout: <disabled-validate-active|direct>
verification: <objective check>
decision:
- <apply|defer|NO_CHANGE>
missing_evidence:
- <none or required artifacts>
Invocation policy
Use before pre-merge governance hardening and before introducing merge queue/ruleset changes across repos.
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.
- 3d ago First seen · 73 lines · 31 tokens per session scan A aa0a7a7c8ebf
github-ruleset-architecture is a skill published in the GitHub repository chf3198/copilot-governance (1 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 472 once invoked, about $0.0002 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…