decision-review

decision-review is a skill for Claude Code, Codex from CATWILLgh/MAINFRAME. It costs 25 tokens per session (1,911 once invoked), scanned A, original, MIT.

A private method for reviewing decisions by testing them against specific, evidence-based ways they could fail. It is used by a dedicated decision-review subagent.

In plain words
What is it for?
Use it to examine a proposed decision, identify grounded failure modes, and state honestly when no serious supported objection was found.
Why use it?
It helps distinguish real, supported objections from guesses or disagreement added only for appearance.

Skill for Claude CodeCodex

Part of the mainframe plugin — 19 skills, 12 hooks shipped together

Install

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.

agentmods
npx agentmods add skills/catwillgh/mainframe/decision-review
Any agent
npx skills add CATWILLgh/MAINFRAME --skill decision-review
Clone the repo
git clone --depth 1 https://github.com/CATWILLgh/MAINFRAME

Made for: Claude Code, Codex.

Or install mainframe, the plugin that ships this one along with the rest of its 19 skills, 12 hooks.

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 decision-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/catwillgh/mainframe/decision-review.svg)](https://agentmods.dev/skills/catwillgh/mainframe/decision-review)
Your own site
<a href="https://agentmods.dev/skills/catwillgh/mainframe/decision-review"><img src="https://agentmods.dev/badge/skills/catwillgh/mainframe/decision-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,911 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00025 $0.01911
Opus 5 $0.00013 $0.00955
Sonnet 5 $0.00005 $0.00382
Haiku 4.5 $0.00003 $0.00191

Measured 4d ago against content hash 9999a0fdd8b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

decision-review 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 4d 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.

adapters/claude-code/plugin/skills/decision-review/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Decision review — method

Read directly by the mainframe-decision-reviewer subagent before every review. Test the proposed decision against its strongest grounded failure modes and report honestly whether they change the decision.

Prime directive — grounding, not posture

The value here is not disagreement itself. Research on assigned devil's advocacy found that it can bolster the initial view rather than produce genuine reconsideration (Nemeth, EJSP 2001). The value is specific, falsifiable, evidence-backed failure modes.

Therefore the one rule that overrides every other:

If you cannot ground an objection in evidence, say so — do not invent one.

State the truth about your own findings: "The strongest objection I can ground is X, severity Medium; beyond that I would be speculating." A reviewer that fabricates plausible-but-false objections trains the reader to ignore it — the false-positive firehose is this method's failure mode, exactly as ritualized dissent is the human one. Honesty about the strength of what you found preserves the signal. Concluding "I found no high-severity grounded objection" is a valid, valuable outcome — not a failure to do your job.

Step 1 — Strip the framing (defeat sycophancy)

RLHF assistants can match a user's expressed beliefs over truthful answers (Anthropic, 2023). Evaluate the artifact, not the author's confidence in it. Ignore enthusiasm, seniority cues, and claims that the answer is obvious. Keep the neutral proposal and judge it against reality, not how it was sold.

Step 2 — Ground yourself in the real system

An objection you can check, you must check. Pure reasoning inherits the same blind spots as the proposal (Huang et al., arXiv:2310.01798 — models cannot reliably self-correct "without external feedback"; tool-grounded critique breaks the loop, Gou et al. CRITIC, arXiv:2305.11738).

  • Read the actual code, configs, and constraints the decision touches (Read/Grep/Glob) before forming objections. A failure mode that the code already prevents is not a failure mode.
  • When the decision rests on a library, framework, protocol, or API claim, verify it against current owning documentation rather than memory. Use Context7 when it exposes the official corpus; otherwise use web search to locate and read the primary source. Add an independent check only when the claim is ambiguous, disputed, plausibly stale, or expensive to get wrong.
  • Tag each objection with its grounding: [code: path:line], [source: url], or [reasoning]. Reasoning-only objections are the weakest and must be flagged as such.

Read the full file on GitHub · 139 lines

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. 4d ago First seen · 139 lines · 25 tokens per session scan A 9999a0fdd8b3

Subscribe to this mod's changes

decision-review is a skill published in the GitHub repository CATWILLgh/MAINFRAME (2 stars, last pushed 14d ago), licensed MIT. It adds 25 tokens to every session and 1,911 once invoked, about $0.0001 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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