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 contactandrewchl-wq/turtle-mcp --skill llm-councilgit clone --depth 1 https://github.com/contactandrewchl-wq/turtle-mcpWrote 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/contactandrewchl-wq/turtle-mcp/llm-council)<a href="https://agentmods.dev/skills/contactandrewchl-wq/turtle-mcp/llm-council"><img src="https://agentmods.dev/badge/skills/contactandrewchl-wq/turtle-mcp/llm-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/contactandrewchl-wq/turtle-mcp/llm-council"><img src="https://agentmods.dev/badge/skills/contactandrewchl-wq/turtle-mcp/llm-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 | $0.00087 | $0.02083 |
| Opus 5 | $0.00044 | $0.01042 |
| Sonnet 5 | $0.00017 | $0.00417 |
| Haiku 4.5 | $0.00009 | $0.00208 |
Grade A, and why
llm-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 11d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Consejo deliberativo (LLM Council, sobre Turtle)
Forzar el desacuerdo productivo antes de decidir. En vez de confiar en la primera respuesta (cómoda y complaciente por defecto), la decisión se somete a cinco voces con perspectivas enfrentadas que la atacan desde ángulos distintos, se revisan entre sí en anónimo, y un presidente sintetiza un veredicto con su próximo paso. El objetivo no es consenso tibio: es exponer el modo de falla, el encuadre equivocado y el punto ciego antes de que cuesten caro.
Cuándo usar
Cuando una decisión cumple al menos una:
- Pesa y es difícil de revertir (arquitectura, modelo de datos, contrato público, elección de stack, pricing).
- Tenés una respuesta y te convence demasiado rápido — señal de juicio rápido, no de análisis.
- El encuadre del problema es dudoso: quizá estás resolviendo la pregunta equivocada.
- Hay sesgo de complacencia: el agente tiende a darte la razón en lugar de discutir.
Si la decisión es trivial, reversible de un commit o ya tiene un camino obvio y barato, no convoques al consejo: decidí directo (ver [[ponytail]]). El consejo cuesta deliberación; usalo donde el error es caro.
Límite de alcance (leer primero)
Este método no spawnea, lanza ni controla procesos, en línea con el SRS §1.2 y con [[agent-orchestration]]:
"TURTLE no es un orquestador que lance o controle agentes; la comunicación entre agentes es asíncrona y mediada por la base de datos."
Las "cinco voces" no son cinco procesos. Son cinco perspectivas. Se materializan de una de dos formas, nunca spawneando:
- Modo mono-sesión (por defecto): una sola sesión recorre las cinco voces como lentes secuenciales (estilo "sombreros de pensamiento"). Barato, sin coordinación externa, sirve para la mayoría de las decisiones.
- Modo por el bus (cuando hay personas activas): el presidente convoca por difusión (
message_send) a personas reales del roster que aportan su voz por la bandeja, de forma asíncrona. Útil cuando la decisión cruza dominios reales (ej. que [[security-owasp]] hable por boca de Raphael). Sigue siendo bus asíncrono: nadie lanza a nadie.
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.
- 11d ago First seen · 103 lines · 87 tokens per session scan A 005f3bdf7359
llm-council is a skill published in the GitHub repository contactandrewchl-wq/turtle-mcp (2 stars, last pushed 2mo ago), licensed MIT. It adds 87 tokens to every session and 2,083 once invoked, about $0.0004 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.
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