ccc-eval

ccc-eval is a command for coding agents from KevinZai/commander. It costs 19 tokens per session (633 once invoked), scanned A, original, MIT.

An evaluation workflow for defining checks before coding, running them, and tracking whether a feature works. It records both new capability checks and checks that protect existing behavior.

In plain words
What is it for?
Use it to create evaluation files, verify feature and regression criteria, and view current pass/fail status.
Why use it?
It makes success criteria explicit before implementation and shows which requirements or regressions still fail.

Command

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/kevinzai/commander/ccc-eval
Clone the repo
git clone --depth 1 https://github.com/KevinZai/commander

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 ccc-eval

README.md
[![agentmods](https://agentmods.dev/badge/commands/kevinzai/commander/ccc-eval.svg)](https://agentmods.dev/commands/kevinzai/commander/ccc-eval)
Your own site
<a href="https://agentmods.dev/commands/kevinzai/commander/ccc-eval"><img src="https://agentmods.dev/badge/commands/kevinzai/commander/ccc-eval.svg" alt="Measured on agentmods" height="20"></a>
Per session 19 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 633 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00019 $0.00633
Opus 5 $0.00010 $0.00316
Sonnet 5 $0.00004 $0.00127
Haiku 4.5 $0.00002 $0.00063

Measured yesterday against content hash 438e511fa60e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ccc-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 yesterday.

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.

commands/ccc-eval.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 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:

  1. 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
  1. Prompt user to fill in specific criteria

Check Evals

/eval check feature-name

Run evals for a feature:

  1. Read eval definition from .claude/evals/feature-name.md
  2. For each capability eval:
    • Attempt to verify criterion
    • Record PASS/FAIL
    • Log attempt in .claude/evals/feature-name.log
  3. For each regression eval:
    • Run relevant tests
    • Compare against baseline
    • Record PASS/FAIL
  4. 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 · 125 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. yesterday First seen · 125 lines · 19 tokens per session scan A 438e511fa60e

Subscribe to this mod's changes

ccc-eval is a command published in the GitHub repository KevinZai/commander (6 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 633 once invoked, about $0.0001 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 2026-09-03.