mainframe-decision-review

mainframe-decision-review is a skill for Claude Code, Codex from CATWILLgh/MAINFRAME. It costs 58 tokens per session (1,111 once invoked), scanned A, original, MIT.

An independent review process for important technical decisions, such as architecture, system design, or a proposed approach.

In plain words
What is it for?
Checking assumptions, comparing alternatives, inspecting affected code and configuration, and deciding whether a proposal should proceed.
Why use it?
It exposes well-supported failure risks and trade-offs before an expensive decision is accepted.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Checking assumptions, comparing alternatives, inspecting affected code and configuration, and deciding whether…

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Install with agentmods
npx agentmods add skills/catwillgh/mainframe/mainframe-decision-review
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.

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

Made for: Claude Code, Codex.

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 mainframe-decision-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/catwillgh/mainframe/mainframe-decision-review.svg)](https://agentmods.dev/skills/catwillgh/mainframe/mainframe-decision-review)
Your own site
<a href="https://agentmods.dev/skills/catwillgh/mainframe/mainframe-decision-review"><img src="https://agentmods.dev/badge/skills/catwillgh/mainframe/mainframe-decision-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,111 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.
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 $0.00058 $0.01111
Opus 5 $0.00029 $0.00556
Sonnet 5 $0.00012 $0.00222
Haiku 4.5 $0.00006 $0.00111

Measured 6d ago against content hash 6a230dbd40a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

mainframe-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 6d 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/codex/skills/mainframe-decision-review/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Decision review

Test the proposed decision against its strongest grounded failure modes. The goal is a more reliable decision, not disagreement for its own sake.

Grounding rule

Ground every material objection in repository evidence, current primary documentation, a bounded experiment, or explicit reasoning. Mark reasoning-only claims as the weakest evidence. If an objection cannot be grounded, discard it and name the limit instead of manufacturing doubt.

Treat a clean review as useful evidence. proceed is the correct verdict when no serious grounded objection survives inspection.

Review method

  1. Reduce the brief to a neutral proposal, its boundary, constraints, viable alternatives, load-bearing assumptions, evidence, and cost of failure. Ignore confidence, enthusiasm, status, and claims that the answer is obvious.
  2. Inspect the affected code, configuration, contracts, and dependency chain before objecting. A failure already prevented by the real system is not a finding. Stay inside the supplied decision boundary.
  3. Verify every version-sensitive framework, library, protocol, API, security, or operational claim against current owning documentation. Use Context7 when it exposes the official corpus; otherwise use live web search to reach the primary source. Add an independent source only when the claim is disputed, interpretive, plausibly stale, or expensive to get wrong.
  4. Run a pre-mortem at a realistic failure horizon: assume the decision failed materially, work backwards to specific causes, then keep only causes that survive grounding.
  5. Try to falsify each load-bearing assumption. State what observation would make it false and whether that observation is present, absent, or still unavailable.
  6. Build the strongest alternative only for a genuine decision fork. Compare it under the same constraints and state where it wins and loses. Do not invent an alternative to fill the report.
  7. Rank surviving objections by consequence and evidence confidence. Stop when the load-bearing assumptions and strongest grounded objections are resolved; more searching is not automatically more confidence.

Read the full file on GitHub · 101 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. 6d ago First seen · 101 lines · 58 tokens per session scan A 6a230dbd40a1

Subscribe to this mod's changes

mainframe-decision-review is a skill published in the GitHub repository CATWILLgh/MAINFRAME (2 stars, last pushed 16d ago), licensed MIT. It adds 58 tokens to every session and 1,111 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.