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 baphuongna/pi-crew --skill councilgit clone --depth 1 https://github.com/baphuongna/pi-crewWrote 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/baphuongna/pi-crew/council)<a href="https://agentmods.dev/skills/baphuongna/pi-crew/council"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/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/skills/baphuongna/pi-crew/council"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/council.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 | $0.00108 | $0.01270 |
| Opus 5.5 | $0.00043 | $0.00508 |
| Sonnet 5.5 | $0.00022 | $0.00254 |
| Haiku 4.5 | $0.00011 | $0.00127 |
Grade A, and why
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 1mo 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Council Pattern — Adversarial Multi-Perspective Decision Making
When to Use
- Evaluating architecture decisions with significant tradeoffs
- Reviewing security-sensitive design choices
- Validating implementation plans before execution
- Resolving ambiguity where multiple valid approaches exist
- Deciding whether to build, buy, or extend
Prerequisites
- A clearly formulated question or decision to evaluate
- Sufficient context about the system for meaningful analysis
Operating Rules
- You MUST spawn exactly 3 subagents with isolated context (fresh, not forked)
- Each subagent receives ONLY the question — NO conversation history (anti-anchoring)
- You MUST NOT influence any subagent's analysis direction
- You MUST record all 3 votes before forming consensus
- You MUST include dissent in the final recommendation
Workflow
Step 1: Formulate the Question
Write a clear, neutral question that includes:
- The decision to be made
- Relevant constraints (performance, security, timeline)
- Available options (if known)
- What "success" looks like
DO NOT bias the question toward any particular answer.
Step 2: Spawn 3 Council Members
Launch 3 parallel subagents, one per seat, using the councillor agents:
- Skeptic (finds flaws) →
subagent_type='councillor-skeptic' - Pragmatist (weighs tradeoffs) →
subagent_type='councillor-pragmatist' - Critic (stress-tests reasoning) →
subagent_type='councillor-critic'
Each subagent's prompt is EXACTLY the question text from Step 1 — nothing else, no context preamble, no your-opinion-matters framing.
The seat perspective, output contract (Position/Confidence/Reasoning + seat-specific field), and anti-anchoring are baked into the agent files. The councillor agents carry inheritProjectContext: false, so isolation is STRUCTURAL (enforced at spawn), not merely instructed — do not wrap the question with your own framing or history.
All three seats return the shared vote block:
Position: PRO | CON | ABSTAIN
Confidence: 0.0-1.0
Reasoning: <analysis>
<Seat-specific field: Top 3 Risks | Alternatives Considered | Hidden Assumptions>
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.
- 1mo ago Changed · -21 lines · +24 tokens per session f11f62e46f59
- 1mo ago First seen · 164 lines · 84 tokens per session scan A c5054fd32ae2
council is a skill published in the GitHub repository baphuongna/pi-crew (59 stars, last pushed today), licensed MIT. It adds 108 tokens to every session and 1,270 once invoked, about $0.0004 per session on Opus 5.5. 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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