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/wyattowalsh/agents/agent-runtime-governancenpx skills add wyattowalsh/agents --skill agent-runtime-governancegit clone --depth 1 https://github.com/wyattowalsh/agentsWrote 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/wyattowalsh/agents/agent-runtime-governance)<a href="https://agentmods.dev/skills/wyattowalsh/agents/agent-runtime-governance"><img src="https://agentmods.dev/badge/skills/wyattowalsh/agents/agent-runtime-governance.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 5.1 | $0.00049 | $0.01509 |
| Opus 5 | $0.00024 | $0.00754 |
| Sonnet 5 | $0.00010 | $0.00302 |
| Haiku 4.5 | $0.00005 | $0.00151 |
Grade A, and why
agent-runtime-governance 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 6d 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Runtime Governance
Design and audit the controls that keep tool-bearing agent systems predictable, observable, and safe to operate.
Scope: Runtime governance for agents that use tools, memory, approvals,
subagents, evals, or external systems. NOT for generic vulnerability scanning
(security-scanner), normal code review (review), prompt-only
optimization (prompt-engineer), or MCP implementation details (mcp-creator).
Dispatch
$ARGUMENTS |
Mode | Action |
|---|---|---|
| Empty | menu |
Show governance modes and required inputs |
design <system> |
design |
Define runtime policies for a new or changing agent system |
audit <path-or-system> |
audit |
Review existing tool, approval, memory, telemetry, and eval controls |
permissions <agent-or-tools> |
permissions |
Design allowlists, denylists, approval modes, and escalation rules |
memory <agent-or-system> |
memory |
Define memory scope, retention, privacy, and invalidation policy |
evals <workflow> |
evals |
Plan regression, adversarial, and runtime acceptance eval loops |
rollout <system> |
rollout |
Define staged release, monitoring, rollback, and operator readiness controls |
incident <failure-mode> |
incident |
Define containment and recovery controls for agent failures |
| Natural language about agent tools, permissions, memory, evals, or containment | Auto-detect the closest mode |
Governance Surfaces
| Surface | Review Questions |
|---|---|
| Tools | Which tools can read, write, spend money, deploy, message users, or delete data? |
| Approvals | Which operations require explicit user approval or human review? |
| Memory | What can be stored, for how long, and at what scope? |
| State | What is durable, replayable, idempotent, and auditable? |
| Telemetry | Which traces, decisions, tool calls, and failures are observable? |
| Evals | Which scenarios prevent regression before rollout? |
| Containment | How does the system stop, rollback, quarantine, or degrade safely? |
What ships with it
11 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.
- evals/evals.json 3.6 KB
- references/control-matrix.md 2.7 KB
- references/rollout-governance.md 1.7 KB
- scripts/asset_toolkit/__init__.py 303 B runs code
- scripts/asset_toolkit/_shared.py 5.6 KB runs code
- scripts/asset_toolkit/common.py 3.0 KB runs code
- scripts/asset_toolkit/package.py 43 KB runs code
- scripts/asset_toolkit/validate_evals.py 11 KB runs code
- scripts/asset_toolkit/validate_hooks.py 13 KB runs code
- scripts/asset_toolkit/validate_skill.py 3.6 KB runs code
- scripts/check.py 1.5 KB runs code
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.
- 6d ago First seen · 158 lines · 49 tokens per session scan A af4911a5e423
agent-runtime-governance is a skill published in the GitHub repository wyattowalsh/agents (5 stars, last pushed 3d ago), licensed MIT. It adds 49 tokens to every session and 1,509 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.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
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…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…