aidoc-flow-framework: Skill for Claude Code

.agents/skills/preprod-review/SKILL.md

preprod-review is a skill for Claude Code, Codex from vladm3105/aidoc-flow-framework. It costs 54 tokens per session (2,294 once invoked), scanned A, original, MIT.

A read-only review process for changes before a release, rollout, deployment, or promotion. It examines the change from several separate viewpoints, checks serious findings against the source, and gives a readiness verdict.

In plain words
What is it for?
Use it before publishing a release, making a shared default, deploying infrastructure, or rolling a change out to many projects.
Why use it?
It helps catch problems before a change reaches more users or systems, when fixing it may be harder or more disruptive. Independent reviews reduce the chance that one reviewer misses an issue.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; installed under .agents/ (shared by several agents).

This is vladm3105/aidoc-flow-framework's own configuration. It tells Claude Code and Codex how to work on aidoc-flow-framework 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 aidoc-flow-framework configures →

Reuse

Borrowing it

Nothing to install: this file belongs to vladm3105/aidoc-flow-framework. 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/vladm3105/aidoc-flow-framework/dev/.agents/skills/preprod-review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/vladm3105/aidoc-flow-framework

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 preprod-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/vladm3105/aidoc-flow-framework/preprod-review/github.svg)](https://agentmods.dev/skills/vladm3105/aidoc-flow-framework/preprod-review)
Your own site
<a href="https://agentmods.dev/skills/vladm3105/aidoc-flow-framework/preprod-review"><img src="https://agentmods.dev/badge/skills/vladm3105/aidoc-flow-framework/preprod-review/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 preprod-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/vladm3105/aidoc-flow-framework/preprod-review"><img src="https://agentmods.dev/badge/skills/vladm3105/aidoc-flow-framework/preprod-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,294 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 $0.00054 $0.02294
Opus 5.5 $0.00022 $0.00918
Sonnet 5.5 $0.00011 $0.00459
Haiku 4.5 $0.00005 $0.00229

Measured 1mo ago against content hash debd0799bf39, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

preprod-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 1mo 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/preprod-review/SKILL.md · 189 lines

How it starts

The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pre-production review

Muse project-skill instance of the canon preprod-review skill. Source: aidoc-flow-claude-agents-config/skills/preprod-review/SKILL.md. Engine-neutral wording mirrors framework/skills/preprod-review/. Skill path in this repo: .agents/skills/preprod-review/. Where the canon names a Claude-specific agent type, use this harness's focused read-only subagent equivalent and keep the independence contract.

Reviewing something well before it ships is not one read — it is several independent reads from angles that a single reviewer conflates and therefore misses. A security lens and a docs lens hunting the same diff surface different truths; fused into one pass they blur. This skill fixes the lenses, runs them in parallel against real source, and forces every surviving finding through a verification step so the verdict is evidence, not vibes.

Use it before anything that widens blast radius:

  • cutting a release or version tag
  • promoting a library, template or workflow to a team/company default
  • rolling a change out to N consumer repos
  • a deploy or infrastructure change that is hard to reverse
  • handing an artifact to adopters who cannot see its internals

Not for ordinary in-flight review of a PR or a work-in-progress branch — that is /code-review. This is for the ship/elevate/rollout decision, where the cost of being wrong is paid by people who were not in the room.

The shape

  1. Scope the surface (you, inline — a few minutes). List every file the review must cover, then read the 2–3 most privileged or most load-bearing ones yourself, so you can spot-check findings later. What counts varies by artifact, but the shape is always entry points, whatever they trust, and the surfaces adopters read:

    Artifact Typically
    CI / workflows .github/workflows/*.yml, install or distribution templates, the scripts they invoke, adopter docs
    library / service public API surface, config and defaults, migration steps, the release or deploy script
    infrastructure the changed resources, IAM/permission boundaries, the state and rollback path
    any of them the governance surfaces — CHANGELOG / ROADMAP / decisions log / handoff
  2. Fan out five lenses in parallel (one dispatch, five agents — see below). Each gets a scoped brief and returns a ranked report. Running them in one turn is the point: they finish together and don't inherit each other's framing.

  3. Synthesize + verify (you, inline). Dedup across the five reports. For every BLOCKER and every HIGH, open the cited file:line and confirm the defect is real before it survives into your output. A plausible-sounding finding that doesn't reproduce against source is noise — cut it or mark it PLAUSIBLE with what would confirm it.

  4. Deliver one ranked verdict: BLOCKER (do not ship), SHIP-WITH-FIXES (fixable, enumerated), or READY. Lead with the verdict, then the ranked findings, then strong positives to not regress.

  5. Promote surviving findings (you, inline — the orchestrator owns this). Lenses must not file; their reports are raw synthesis input. Check every surviving BLOCKER and HIGH against the submit-feedback promotion bar and file the ones that clear it via submit-feedback (search-first, body contract, safe publication). Link the issue numbers from the verdict so no finding dies at the transcript boundary.

Read the full file on GitHub · 189 lines

Files

What ships with it

2 files 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. 1mo ago First seen · 189 lines · 54 tokens per session scan A debd0799bf39

Subscribe to this mod's changes

preprod-review is a skill published in the GitHub repository vladm3105/aidoc-flow-framework (17 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 2,294 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-28.