A command for eval-driven development, where a feature is described with capability checks and regression checks before its results are recorded and reviewed.

Use it to define evaluation criteria, check whether capabilities and regressions pass, record attempts, and report the current status of a feature.

It makes feature success and preservation of existing behavior explicit instead of relying only on informal judgment.

eval — Command for coding agents by JSK9999: A command for eval-driven development, where a feature is…

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/jsk9999/ai-nexus/eval

Clone the repo

git clone --depth 1 https://github.com/JSK9999/ai-nexus

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/jsk9999/ai-nexus/eval.svg)](https://agentmods.dev/commands/jsk9999/ai-nexus/eval)

Your own site

<a href="https://agentmods.dev/commands/jsk9999/ai-nexus/eval"><img src="https://agentmods.dev/badge/commands/jsk9999/ai-nexus/eval.svg" alt="Measured on agentmods" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 609 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 89% 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	$0.00000	$0.00609
Opus 5	$0.00000	$0.00304
Sonnet 5	$0.00000	$0.00122
Haiku 4.5	$0.00000	$0.00061

Measured 4d ago against content hash 7c8e20c65995, 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 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.

Origin

This is a copy

89% identical to eval — 4 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.

config/commands/eval.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Eval Command

Manage eval-driven development workflow.

Usage

/eval [define|check|report|list] [feature-name]

Define Evals

/eval define feature-name

Create a new eval definition:

Create .claude/evals/feature-name.md with template:

## EVAL: feature-name
Created: $(date)

### Capability Evals
- [ ] [Description of capability 1]
- [ ] [Description of capability 2]

### Regression Evals
- [ ] [Existing behavior 1 still works]
- [ ] [Existing behavior 2 still works]

### Success Criteria
- pass@3 > 90% for capability evals
- pass^3 = 100% for regression evals

Prompt user to fill in specific criteria

Check Evals

/eval check feature-name

Run evals for a feature:

Read eval definition from .claude/evals/feature-name.md
For each capability eval:
- Attempt to verify criterion
- Record PASS/FAIL
- Log attempt in .claude/evals/feature-name.log
For each regression eval:
- Run relevant tests
- Compare against baseline
- Record PASS/FAIL
Report current status:

EVAL CHECK: feature-name
========================
Capability: X/Y passing
Regression: X/Y passing
Status: IN PROGRESS / READY

Report Evals

/eval report feature-name

Generate comprehensive eval report:

EVAL REPORT: feature-name
=========================
Generated: $(date)

CAPABILITY EVALS
----------------
[eval-1]: PASS (pass@1)
[eval-2]: PASS (pass@2) - required retry
[eval-3]: FAIL - see notes

REGRESSION EVALS
----------------
[test-1]: PASS
[test-2]: PASS
[test-3]: PASS

METRICS
-------
Capability pass@1: 67%
Capability pass@3: 100%
Regression pass^3: 100%

NOTES
-----
[Any issues, edge cases, or observations]

RECOMMENDATION
--------------
[SHIP / NEEDS WORK / BLOCKED]

List Evals

/eval list

Show all eval definitions:

EVAL DEFINITIONS
================
feature-auth      [3/5 passing] IN PROGRESS
feature-search    [5/5 passing] READY
feature-export    [0/4 passing] NOT STARTED

Arguments

$ARGUMENTS:

define <name> - Create new eval definition
check <name> - Run and check evals
report <name> - Generate full report
list - Show all evals
clean - Remove old eval logs (keeps last 10 runs)

Read the full file on GitHub · 121 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.

4d ago First seen · 121 lines · 0 tokens per session scan A 7c8e20c65995

Subscribe to this mod's changes

eval is a command published in the GitHub repository JSK9999/ai-nexus (19 stars, last pushed 5mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 609 tokens. A static security scan graded it A with 0 findings. It is 89% identical to eval, differing in 4 lines, and is treated as a copy.

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