audit-functional-suitability

audit-functional-suitability is a skill for Claude Code, Codex from tomzx/agents. It costs 132 tokens per session (1,801 once invoked), scanned A, original, MIT.

A review of whether the software implements its required behavior completely, correctly, and appropriately. It compares the code with requirements and looks for unfinished or disabled work.

In plain words
What is it for?
Use it to check a repository against requirements stored in .sdlc files and to identify missing code, unfinished implementations, disabled tests, and related functional gaps.
Why use it?
It catches features that were promised but not implemented, incomplete behavior, stubs, TODOs, disabled tests, and other signs that the code does not match its requirements.

Skill for Claude CodeCodex

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/tomzx/agents/audit-functional-suitability
Any agent
npx skills add tomzx/agents --skill audit-functional-suitability
Clone the repo
git clone --depth 1 https://github.com/tomzx/agents

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 audit-functional-suitability

README.md
[![agentmods](https://agentmods.dev/badge/skills/tomzx/agents/audit-functional-suitability.svg)](https://agentmods.dev/skills/tomzx/agents/audit-functional-suitability)
Your own site
<a href="https://agentmods.dev/skills/tomzx/agents/audit-functional-suitability"><img src="https://agentmods.dev/badge/skills/tomzx/agents/audit-functional-suitability.svg" alt="Measured on agentmods" height="20"></a>
Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,801 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 5.1 $0.00132 $0.01801
Opus 5 $0.00066 $0.00901
Sonnet 5 $0.00026 $0.00360
Haiku 4.5 $0.00013 $0.00180

Measured 5d ago against content hash 31ec75ceafe8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

audit-functional-suitability 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 5d 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.

skills/audit-functional-suitability/SKILL.md · 168 lines

How it starts

The opening of the file, as written. The whole thing — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.

TODAY=!date +%Y-%m-%d

Functional Suitability Audit (ISO/IEC 25010)

Audits the codebase for functional suitability: does the software provide the functions needed to meet stated requirements, completely and correctly? It is the bottom-up check that what was supposed to be built is actually built and working.

This is the Functional suitability characteristic of the ISO/IEC 25010 quality model. Distinct from check-issue-status (which checks whether a single issue is addressed), this audit scans the whole implementation against its requirements corpus and the code's own honesty markers (stubs, TODOs, disabled tests).

Prerequisites

  • Working directory is the root of the repository
  • .sdlc/features/*/requirements.md present (improves completeness scoring; if absent, the audit falls back to code-honesty signals only)
  • Read .sdlc/context/project-overview.md if present for scope
  • gh CLI for open bug-issue signals (optional)

What This Checks

Sub-characteristic What it means Signals scanned
Functional completeness All required functions are implemented requirements with no matching code; TODO/FIXME/NotImplemented/stub/501/raise NotImplementedError; feature flags wired but never enabled
Functional correctness Functions produce correct results open bug issues; skipped/disabled/xfail tests; assertion-free tests; logic that silently no-ops (empty except, return None on happy paths)
Functional appropriateness Functions are suitable for the intended use requirements whose implementation exists but diverges from the stated acceptance criteria; over-broad or surprising behavior

Steps

1. Inventory requirements (if .sdlc exists)

For each .sdlc/features/*/requirements.md, extract functional requirements (FR-N) and their acceptance criteria. Record each as a completeness target.

find .sdlc/features -name requirements.md 2>/dev/null

Read the full file on GitHub · 168 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. 5d ago First seen · 168 lines · 132 tokens per session scan A 31ec75ceafe8

Subscribe to this mod's changes

audit-functional-suitability is a skill published in the GitHub repository tomzx/agents (6 stars, last pushed yesterday), licensed MIT. It adds 132 tokens to every session and 1,801 once invoked, about $0.0007 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

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…

microsoft/ai-agents-for-beginners · 200 tokens

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…

vercel/next.js · 95 tokens

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…

vercel/next.js · 170 tokens

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…

vercel/next.js · 103 tokens

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…

microsoft/vscode · 72 tokens