A command for checking an implementation against written acceptance criteria, which are the conditions a feature must meet. It can use pass/fail, numeric, or category-based scoring.

Use it after implementing a feature to define criteria, run relevant tests, calculate a score, and produce an evaluation report.

It turns a broad review into a documented comparison between requirements, tests, evidence, and results. This makes it easier to see what is complete and what still needs work.

eval — Command for coding agents by SiniyaYousuf: A command for checking an implementation against written acceptance…

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 commands/siniyayousuf/everything_claudecode/eval

Clone the repo

git clone --depth 1 https://github.com/SiniyaYousuf/everything_claudecode

Or install everything-claude-code, the plugin that ships this one along with the rest of its 29 skills, 29 commands.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/siniyayousuf/everything_claudecode/eval.svg)](https://agentmods.dev/commands/siniyayousuf/everything_claudecode/eval)

Your own site

<a href="https://agentmods.dev/commands/siniyayousuf/everything_claudecode/eval"><img src="https://agentmods.dev/badge/commands/siniyayousuf/everything_claudecode/eval.svg" alt="Measured on agentmods" height="20"></a>

Per session 5 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 445 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 100% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5	$0.00005	$0.00445
Opus 5	$0.00003	$0.00222
Sonnet 5	$0.00001	$0.00089
Haiku 4.5	$0.00001	$0.00044

Measured 3d ago against content hash b090a6524c94, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

eval 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.

Origin

This is a copy

100% identical to eval — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.opencode/commands/eval.md · 89 lines

What it actually says

Eval Command

Evaluate implementation against acceptance criteria: $ARGUMENTS

Your Task

Run structured evaluation to verify the implementation meets requirements.

Evaluation Framework

Grader Types

Binary Grader - Pass/Fail
- Does it work? Yes/No
- Good for: feature completion, bug fixes
Scalar Grader - Score 0-100
- How well does it work?
- Good for: performance, quality metrics
Rubric Grader - Category scores
- Multiple dimensions evaluated
- Good for: comprehensive review

Evaluation Process

Step 1: Define Criteria

Acceptance Criteria:
1. [Criterion 1] - [weight]
2. [Criterion 2] - [weight]
3. [Criterion 3] - [weight]

Step 2: Run Tests

For each criterion:

Execute relevant test
Collect evidence
Score result

Step 3: Calculate Score

Final Score = Σ (criterion_score × weight) / total_weight

Step 4: Report

Evaluation Report

Overall: [PASS/FAIL] (Score: X/100)

Criterion Breakdown

Criterion	Score	Weight	Weighted
[Criterion 1]	X/10	30%	X
[Criterion 2]	X/10	40%	X
[Criterion 3]	X/10	30%	X

Evidence

Criterion 1: [Name]

Test: [what was tested]
Result: [outcome]
Evidence: [screenshot, log, output]

Recommendations

[If not passing, what needs to change]

Pass@K Metrics

For non-deterministic evaluations:

Run K times
Calculate pass rate
Report: "Pass@K = X/K"

TIP: Use eval for acceptance testing before marking features complete.

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.

3d ago First seen · 89 lines · 5 tokens per session scan A b090a6524c94

Subscribe to this mod's changes

eval is a command published in the GitHub repository SiniyaYousuf/everything_claudecode (14 stars, last pushed 5mo ago), licensed MIT. It adds 5 tokens to every session and 445 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to eval, differing in 0 lines, and is treated as a copy.

Testing

eval