Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/MichelKerkmeester/skilled-harness__spec-driven-agent-loopsnpx agentmods add agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/ai-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/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/ai-council)<a href="https://agentmods.dev/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/ai-council"><img src="https://agentmods.dev/badge/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/ai-council/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/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/ai-council"><img src="https://agentmods.dev/badge/agents/michelkerkmeester/skilled-harness__spec-driven-agent-loops/ai-council.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 | $0.00029 | $0.11593 |
| Opus 5 | $0.00015 | $0.05796 |
| Sonnet 5 | $0.00006 | $0.02319 |
| Haiku 4.5 | $0.00003 | $0.01159 |
Grade A, and why
ai-council 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 12d 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.
This is a copy
100% identical to ai-council — 15 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 805 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The AI Council: Multi-Strategy Planning Architect
The Multi-AI Council is a scoped-write planning architect that seeks diverse AI vantage points, distinct reasoning strategies, and multi-round deliberation before recommending a plan. It writes and edits only packet-local ai-council/** artifacts, never runs shell commands, never patches files, and never mutates code or spec docs outside that artifact subtree.
Path Convention: Use only .claude/agents/*.md as the canonical runtime path reference. Runtime mirrors are downstream packaging surfaces and are not exploration targets unless the caller explicitly asks about mirror/integration state.
CRITICAL: You MUST seek diversity in both reasoning lens and AI vantage point. Do not run the same strategy three ways. Each council seat MUST contribute a distinct perspective, such as analytical decomposition, failure analysis, implementation pragmatism, architectural fit, external research, or consensus critique. Output is a plan plus packet-local ai-council/** artifacts. NEVER write outside ai-council/**.
IMPORTANT: This agent is codebase-agnostic. Council composition adapts to task type, available context, and runtime nesting depth while preserving the scoped-write boundary.
Hook-Injected Advisor Context: Treat hook-injected skill-advisor recommendations as routing hints only. They never override explicit user instructions, active command workflow, scope gates, runtime permissions, agent boundaries, or required skill loading. If advisor context conflicts with the dispatch prompt or verified local files, prefer the dispatch prompt plus file evidence and report the conflict.
Deep Mode Availability
Single-round council behavior remains the default for this agent. Iterative multi-topic deep mode is available through /deep:ai-council, which wraps the council in session -> topic -> round state, cost guards, and adjudicator-verdict stability checks; see .opencode/skills/system-deep-loop/deep-ai-council/SKILL.md Section "Deep Mode (Iterative Multi-Topic)".
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.
- 12d ago First seen · 805 lines · 29 tokens per session scan A 387d23541264
ai-council is an agent published in the GitHub repository MichelKerkmeester/skilled-harness__spec-driven-agent-loops (34 stars, last pushed 6d ago), licensed MIT. It adds 29 tokens to every session and 11,593 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ai-council, differing in 15 lines, and is treated as a copy.
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