ai-engineering: Skill for Claude Code

.agents/skills/ai-council/SKILL.md

ai-council is a skill for Claude Code from arcasilesgroup/ai-engineering. It costs 182 tokens per session (1,420 once invoked), scanned A, original, Apache-2.0.

A specification-review process that examines one document through five independent viewpoints, then cross-checks their findings and writes a final verdict into the specification.

In plain words
What is it for?
Use it to review a specification from several angles and record the verdict, recommendation, first step, and supported findings in the document itself.
Why use it?
It exposes costs, risks, assumptions, undecided paths, and missing examples that one reviewer may overlook, without letting reviewers influence one another too early.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is arcasilesgroup/ai-engineering's own configuration. It tells Claude Code how to work on ai-engineering itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-engineering configures →

Reuse

Borrowing it

Nothing to install: this file belongs to arcasilesgroup/ai-engineering. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/arcasilesgroup/ai-engineering/main/.agents/skills/ai-council/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/arcasilesgroup/ai-engineering

Made for: Claude Code.

Wrote 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.

agentmods badge for ai-council

README.md
[![agentmods](https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-council/github.svg)](https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-council)
Your own site
<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-council"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/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.

agentmods 80×15 button for ai-council

Your own site · 80×15
<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-council"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-council.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 182 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,420 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00182 $0.01420
Opus 5 $0.00091 $0.00710
Sonnet 5 $0.00036 $0.00284
Haiku 4.5 $0.00018 $0.00142

Measured 9d ago against content hash 605d2710bf4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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 9d 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.

.agents/skills/ai-council/SKILL.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

One pass: five lenses, one cross-read, a verdict inside the spec

What it produces

The specification's ## Council section: three machine-read headings, the two counts, a verdict, a recommendation and one first step. No transcript file and no page beside it — the section is the record and the record is the artifact.

The lenses, and none of them sees another

Cost, reversibility, the undecidable path, what is taken on trust, the example nobody wrote. Each is a question, not a personality. Each reads the spec and nothing else. Not the plan, not the chat, not another lens's answer.

That rule is not taste. Put one answer in a reader's context and a right answer turns wrong 66.5% of the time, against 10.3% for a plain re-ask (report 003). Nobody was named as its author. So the harm comes from the words being there, not from being told who wrote them.

Reading alone also buys ground. Human reviewers who do not confer raise 14 issues a session against 9 (report 003). And 70% (report 003) of what they find is seen by one reader only.

Every finding carries a command a reader can run to see the gap. One with no command is cut before its section is written, and it is listed under its own heading below so the count can be recomputed rather than believed.

The cross-read, inside the same pass

Each lens then sees the other four answers, relabelled and shuffled, and not its own. It answers two questions. Which of these findings is a false alarm, and what command shows it? And what did all of us miss?

It is never asked which answer is best. Ranking five good answers is the worst case in the measured work: one judge falls from 0.70 to 0.34 moving from pairs to a list (report 003). What the cross-read buys is aim: false alarms fall from 22% to 5.3% (report 003), and no true finding is lost.

A refutation carries a command. The command is run and its output is written down. One with no command is dropped, the same way a finding with none is.

A refuted finding is struck through and kept, with the refuting command beside it. It is never erased: a real gap killed by a good-looking answer must leave more than a number. Where one lens refutes and another agrees, the finding stays under the gaps and is not also listed under the refuted heading — one heading owns one finding, or the two counts double-count what the counter exists to keep honest.

Read the full file on GitHub · 119 lines

Files

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.

Changes

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.

  1. 9d ago First seen · 119 lines · 182 tokens per session scan A 605d2710bf4a

Subscribe to this mod's changes

ai-council is a skill published in the GitHub repository arcasilesgroup/ai-engineering (54 stars, last pushed yesterday), licensed Apache-2.0. It adds 182 tokens to every session and 1,420 once invoked, about $0.0009 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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