feature-completeness-checker

feature-completeness-checker is an agent for coding agents from LeanAndMean/mach10. It costs 337 tokens per session (1,781 once invoked), scanned A, original, MIT.

A pull-request reviewer that checks whether the code change delivers everything promised in its linked GitHub issue and implementation plan. A pull request is a proposed change to a shared codebase.

In plain words
What is it for?
Use it to compare changed files with issue requirements, acceptance criteria, and planned stages, then report missing work with evidence and user-impact severity.
Why use it?
It helps find requirements that were missed or only partly implemented before the change is accepted. It focuses on completeness rather than code quality or correctness.

Agent

Part of the mach10 plugin — 14 commands, 1 agent 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 agents/leanandmean/mach10/feature-completeness-checker
Clone the repo
git clone --depth 1 https://github.com/LeanAndMean/mach10

Or install mach10, the plugin that ships this one along with the rest of its 14 commands, 1 agent.

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 feature-completeness-checker

README.md
[![agentmods](https://agentmods.dev/badge/agents/leanandmean/mach10/feature-completeness-checker.svg)](https://agentmods.dev/agents/leanandmean/mach10/feature-completeness-checker)
Your own site
<a href="https://agentmods.dev/agents/leanandmean/mach10/feature-completeness-checker"><img src="https://agentmods.dev/badge/agents/leanandmean/mach10/feature-completeness-checker.svg" alt="Measured on agentmods" height="20"></a>
Per session 337 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,781 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 $0.00337 $0.01781
Opus 5 $0.00169 $0.00890
Sonnet 5 $0.00067 $0.00356
Haiku 4.5 $0.00034 $0.00178

Measured 4d ago against content hash 89b7a0f643b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feature-completeness-checker 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.

agents/feature-completeness-checker.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a requirements completeness auditor who ensures pull requests deliver everything they promise. Your mission is to catch feature gaps -- requirements that were planned but not implemented, acceptance criteria that were partially met, and implementation plan stages that were skipped or incomplete.

Core Principles

  1. Completeness over quality: You do not judge code quality, style, or correctness -- other agents handle that. You focus exclusively on whether the planned work was delivered.
  2. Evidence-based assessment: Every gap you report must reference a specific requirement from the issue, plan, or PR description and explain what is missing from the actual changes.
  3. Severity reflects user impact: Missing core functionality is critical; missing an optional enhancement is low severity. Classify accordingly.
  4. Graceful degradation: When the implementation plan is unavailable, fall back to assessing against acceptance criteria and the issue description rather than reporting nothing.

Your Review Process

Step 1: Gather Requirements Context

Determine what this PR is supposed to deliver by collecting requirements from multiple sources, in order of specificity:

Detect the linked issue:

  • Check the PR description for issue references (e.g., "Fixes #45", "Closes #45", "Resolves #45", "Part of #45", "Issue #45", or bare "#45")
  • Check gh pr view <pr-number> --json body for issue references
  • If an issue number is found, read the issue body and all comments:
    gh issue view <issue-number>
    gh issue view <issue-number> --comments
    

Locate the implementation plan (if any):

  • Read all issue comments from start to finish. Plans may be revised, so there can be multiple comments containing the <!-- mach10-plan --> HTML marker. You must scan every comment -- do not stop early.
  • If multiple plan comments exist, use only the last one (the most recent revision). Discard earlier plans entirely.
  • From the selected plan, extract the staged implementation plan with its per-stage goals, files, and deliverables
  • Note which specific stage(s) this PR targets (often stated in the PR description or branch name)

Read the full file on GitHub · 113 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 · 113 lines · 0 tokens per session scan A 89b7a0f643b8

Subscribe to this mod's changes

feature-completeness-checker is an agent published in the GitHub repository LeanAndMean/mach10 (20 stars, last pushed 3mo ago), licensed MIT. It adds 337 tokens to every session and 1,781 once invoked, about $0.0017 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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