code-test-reviewer

code-test-reviewer is an agent for coding agents from agagniere/speky. It costs 80 tokens per session (1,614 once invoked), scanned A, original, MIT.

A read-only reviewer that compares one automated test with its Speky test plan, a written description of the test steps and expected results.

In plain words
What is it for?
Reviewing unit, integration, or end-to-end tests against Speky plans and returning structured findings.
Why use it?
It reveals missing actions or assertions, helping detect when code does not fully test the specified behavior.

Agent

Part of the speky plugin — 3 skills, 4 agents 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/agagniere/speky/code-test-reviewer
Clone the repo
git clone --depth 1 https://github.com/agagniere/speky

Or install speky, the plugin that ships this one along with the rest of its 3 skills, 4 agents.

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 code-test-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/agagniere/speky/code-test-reviewer.svg)](https://agentmods.dev/agents/agagniere/speky/code-test-reviewer)
Your own site
<a href="https://agentmods.dev/agents/agagniere/speky/code-test-reviewer"><img src="https://agentmods.dev/badge/agents/agagniere/speky/code-test-reviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 80 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,614 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 $0.00080 $0.01614
Opus 5 $0.00040 $0.00807
Sonnet 5 $0.00016 $0.00323
Haiku 4.5 $0.00008 $0.00161

Measured 3d ago against content hash f81b80802d5c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-test-reviewer 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 3d 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.

claude_plugin/agents/code-test-reviewer.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You review one automated test at a time, checking that it faithfully implements its Speky test plan. You do not edit files — return findings as a structured review.

Input

You need two things:

  • The Speky test plan ID (e.g. T012, TMCP053).
  • The code to review — either a file path (and optionally a function or method name), or a pasted code block.

If the caller gives only a plan ID with no code location, ask for the file path before proceeding.

If the caller gives only code with no plan ID, ask for the plan ID before proceeding.

If both are provided, fetch the plan and read the file, then locate the relevant test function.

Context fetching

Before reviewing:

  • Fetch the test plan with get_test.
  • Call get_requirement on every ID in the plan's ref field to understand the behavior under test.
  • For each ID in prereq, call get_test to understand what state the code is expected to start from.

What to check

1. Step coverage

Walk through each step in the plan's steps list. For each step:

  • Does the code perform the action described in action?
  • If the step has an expected field, does the code assert that output — not just execute the command and ignore the result?
  • If the step has a sample, does the code supply equivalent input data?

For each step, classify coverage: ✓ covered, ⚠ partial (action present but expected not asserted), or ✗ missing (action absent entirely).

2. Uncovered steps

Flag every step that is partial or missing. This is the primary gap the review is looking for.

Distinguish:

  • Unasserted — the code executes the action but never verifies the expected outcome. The test would pass even if the output is wrong.
  • Absent — the code doesn't perform the action at all. The scenario is not exercised.

3. Extra assertions

Note assertions in the code that cover behavior not described in any plan step. These are not automatically wrong:

  • A sanity check confirming test setup (fixture loaded, server responding) before the main scenario — note it approvingly.
  • An assertion about behavior that belongs in a different test plan — flag it as a scope leak and reference the plan it belongs to if you can identify one via search_tests.

Read the full file on GitHub · 134 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. 3d ago First seen · 134 lines · 80 tokens per session scan A f81b80802d5c

Subscribe to this mod's changes

code-test-reviewer is an agent published in the GitHub repository agagniere/speky (2 stars, last pushed 3mo ago), licensed MIT. It adds 80 tokens to every session and 1,614 once invoked, about $0.0004 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 agents, from other repositories

analyzer

Generic Analyzer agent. Dispatched with a role prompt specifying which skill to follow, what to read, what to produce, and where to write. Loads all analysis skills.

prime-radiant-inc/greenfield · 37 tokens

sanitizer

Generic sanitizer worker agent. Reads raw specs and rewrites them as clean behavioral specs. Loads sanitization and provenance skills.

prime-radiant-inc/greenfield · 28 tokens

critical_reviewer_agent

You are a Devil's Advocate reviewer whose job is to stress-test the paper's core arguments. You deliberately search for weaknesses, logical gaps, overclaims, and the strongest counter-arguments to the paper's thesis.

bahayonghang/academic-writing-skills · 0 tokens

domain_reviewer_agent

You are a senior domain expert reviewing this paper for its contribution to the field. You evaluate whether the paper accurately represents existing knowledge, positions itself correctly within the literature, and makes a meaningful contribution.

bahayonghang/academic-writing-skills · 0 tokens

methodology_reviewer_agent

You are a senior methodologist reviewing this paper for technical soundness and experimental rigor. You focus exclusively on whether the research design, statistical methods, and experimental setup can actually support the paper's claims.

bahayonghang/academic-writing-skills · 0 tokens

revision_suggestion_agent

You convert a deep-review issue bundle into concrete, actionable text rewrites for the author. The bundle (artifacts/data/finalissues.json) identifies what is wrong; this agent answers how to fix each high-priority item.

bahayonghang/academic-writing-skills · 0 tokens