Borrowing it
Nothing to install: this file belongs to nbiish/agentsstandard-dot-com. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nbiish/agentsstandard-dot-com/main/.agents/skills/advisory-council/SKILL.mdgit clone --depth 1 https://github.com/nbiish/agentsstandard-dot-comWrote 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/nbiish/agentsstandard-dot-com/advisory-council)<a href="https://agentmods.dev/skills/nbiish/agentsstandard-dot-com/advisory-council"><img src="https://agentmods.dev/badge/skills/nbiish/agentsstandard-dot-com/advisory-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/nbiish/agentsstandard-dot-com/advisory-council"><img src="https://agentmods.dev/badge/skills/nbiish/agentsstandard-dot-com/advisory-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 | $0.00067 | $0.08971 |
| Opus 5 | $0.00034 | $0.04485 |
| Sonnet 5 | $0.00013 | $0.01794 |
| Haiku 4.5 | $0.00007 | $0.00897 |
Grade A, and why
advisory-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 8d 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 — 393 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advisory Council
20 expert identities dispatched as sub-agents. Each inherits a full persona, analyzes the query through their unique lens, and appends to a single deliberation document. The orchestrator synthesizes all perspectives into a final recommendation.
Dispatch Protocol
- Select experts relevant to the query (minimum 3, maximum 20)
- Create deliberation file at
/tmp/council-{timestamp}.mdwith header (query, date, experts) - Dispatch sub-agents — each reads the expert profile below, adopts that identity, analyzes the query, and appends their section to the shared file
- Synthesize after all experts contribute: consensus, disagreements, risks, final recommendation
Selection Guide
| Query Type | Recommended Experts |
|---|---|
| Investment / stock analysis | All 13 personas + 7 analytical agents |
| Risk assessment | taleb, burry, pabrai, risk, fundamentals, technicals |
| Growth / opportunity | wood, fisher, lynch, druckenmiller, growth, valuation |
| Value hunting | graham, buffett, munger, burry, damodaran, fundamentals, valuation |
| Strategic business decision | buffett, munger, ackman, druckenmiller, taleb, risk |
| General question | 5-8 most relevant by topic |
| Quick sanity check | buffett, taleb, lynch, fundamentals, risk |
Sub-Agent Prompt Template
For each expert, dispatch a Task (subagent_type: general-purpose) with this prompt:
You are {EXPERT_NAME}. {IDENTITY}
{THINKING_FRAMEWORK}
{METHODOLOGY}
Voice: {COMMUNICATION_STYLE}
QUERY: {USER_QUERY}
{CONTEXT}
Append your analysis to {DELIBERATION_FILE}. Start with:
## {EXPERT_NAME} — {ARCHETYPE}
Provide: Assessment, Key Metrics/Factors, Signal (bullish/bearish/neutral), Confidence (0-100), Reasoning.
Synthesis Template (append after all experts)
## Council Synthesis
### Consensus View — {what majority agrees on}
### Key Disagreements — {where experts diverge and why}
### Risk Assessment — {primary risks across perspectives}
### Final Recommendation — {synthesized view with confidence}
### Signal Distribution
| Expert | Signal | Confidence |
What ships with it
1 file 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.
- 8d ago First seen · 393 lines · 67 tokens per session scan A 702546f611e4
advisory-council is a skill published in the GitHub repository nbiish/agentsstandard-dot-com (2 stars, last pushed 3mo ago), licensed MIT. It adds 67 tokens to every session and 8,971 once invoked, about $0.0003 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…
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…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
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…