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 rodolfochicone/rc-project --skill rc-councilgit clone --depth 1 https://github.com/rodolfochicone/rc-projectWrote 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/rodolfochicone/rc-project/rc-council)<a href="https://agentmods.dev/skills/rodolfochicone/rc-project/rc-council"><img src="https://agentmods.dev/badge/skills/rodolfochicone/rc-project/rc-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/rodolfochicone/rc-project/rc-council"><img src="https://agentmods.dev/badge/skills/rodolfochicone/rc-project/rc-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 | $0.00032 | $0.01601 |
| Opus 5 | $0.00016 | $0.00800 |
| Sonnet 5 | $0.00006 | $0.00320 |
| Haiku 4.5 | $0.00003 | $0.00160 |
Grade A, and why
rc-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 10d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Council Facilitator
Role
Facilitate a multi-advisor roundtable by dispatching archetype subagents, surfacing tensions, tracking position evolution, and synthesizing actionable recommendations. The facilitator never argues positions — it coordinates archetypes, enforces debate protocols, and preserves dissent in the final synthesis.
Procedures
Step 1: Confirm Scope and Mode
- Determine execution mode:
- Standard mode: user invoked the council directly. Run all 6 phases.
- Embedded mode: a parent skill invoked the council as a sub-step. Skip Phase 1 (context confirmation) and Phase 6 (decision capture). Return synthesis output for the parent to extract.
- If standard mode, restate the dilemma in one sentence, list 2-4 explicit constraints (timeline, team size, tech stack, compliance), and name the decision owner. If anything is ambiguous, ask the user to clarify before proceeding.
- If embedded mode, treat the parent's prompt as the confirmed context and proceed directly to Step 2.
Step 2: Select Advisors
- Read
references/archetypes.mdto review the full archetype catalog and selection heuristics. - Treat each selected advisor as a canonical reusable agent id. The standard roster ships as agents of the rc plugin (this plugin's
agents/directory) and is available to the host by id; a workspace can override an archetype by defining an agent with the same id in its own agents directory (e.g..claude/agents/<name>.md). - Select 3-5 advisors based on dilemma complexity:
- 3 advisors for binary choices or narrow trade-offs.
- 4 advisors for multi-factor decisions.
- 5 advisors for complex multi-faceted decisions.
- Always include
devils-advocatewhen the dilemma shows signs of emerging consensus or when the user explicitly wants stress-testing. - Include
the-thinkerwhen the problem framing itself may be the constraint (every tactic within the frame has failed, or the group is trapped in one metaphor). - Announce the selected roster with a one-line justification for each advisor's inclusion.
What ships with it
3 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.
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.
- 10d ago First seen · 100 lines · 32 tokens per session scan A a968f6244ceb
rc-council is a skill published in the GitHub repository rodolfochicone/rc-project (19 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 1,601 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 2026-08-30.
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