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eval

/eval

Eval-driven development for AI features. Triggers on /codeforge:eval or when any LLM-powered feature, prompt, or agent changes. Define pass/fail before implementing.

Repository
codeforge ↗
Licence
MIT
Last repository change
26.06.2026

Assessment and security

100/ 100Class: good
Format25 / 25
Frontmatter with name and description, valid name, description up to 1,024 characters, name matching the folder.
Discoverability25 / 25
Description explains when to use the skill, has a reasonable length and uses third person.
Content35 / 35
At least 150 words and at most 500 lines, headings, step lists, examples or code.
Hygiene15 / 15
No placeholders such as TODO, no Windows paths, with a licence.
Riskno signals detected in the scan
Files in this package
2
Scripts
0
HTML comments
0
URLs in SKILL.md
0
Deprecation

No signals detected. Repository changed on 26.06.2026, without references to retired models or APIs.

Licence

MIT, open: use and modify while retaining author attribution.

What it does and when to use it

Eval-driven development for AI features. Triggers on /codeforge:eval or when any LLM-powered feature, prompt, or agent changes. Define pass/fail before implementing.

Original author description

Eval-driven development for AI features. Triggers on /codeforge:eval or when any LLM-powered feature, prompt, or agent changes. Define pass/fail before implementing.

How it works

  1. Workflow
  2. Eval spec format
  3. Grader types
  4. Metrics
  5. Report format
Original SKILL.md headings · 50 lines, 219 words
SKILL.md preview
---
name: eval
description: Eval-driven development for AI features. Triggers on /codeforge:eval or when any LLM-powered feature, prompt, or agent changes. Define pass/fail before implementing.
allowed-tools: Read, Write, Edit, Bash, Grep, Glob
---

# codeforge:eval

## Workflow

| Phase | Action | Gate |
|-------|--------|------|
| DEFINE | Write eval spec before any code | **STOP: show user, wait for approval** |
| IMPLEMENT | Write code/prompts to pass the spec | n/a |
| GRADE | Run graders, measure pass@k | n/a |
| REPORT | Compare to baseline, flag regressions | Block on any regression |

## Eval spec format

```markdown
## EVAL: <feature-name>
### Capability
- [ ] <what must succeed>
### Regression
- [ ] <existing behavior that must not break>
### Metrics
- Capability: pass@3 > 90%
- Regression: pass^3 = 100%
```
Save at `.claude/evals/<feature-name>.md`.

## Grader types

| Output | Grader | Example |
|--------|--------|---------|
| Deterministic | Code (bash) | `npm test && echo PASS \|\| echo FAIL` |
| Open-ended | Model prompt | Rate 1-3: solves problem / correct format / handles edges |

## Metrics

| Metric | Meaning | Target |
|--------|---------|--------|
| pass@1 | First-attempt success | > 70% |
| pass@3 | At least 1 success in 3 | > 90% |
| pass^3 | All 3 succeed | 100% on critical paths |

## Report format

```
FORGE EVAL — <date>
Feature       Capability    Regression    Status
<name>        X/Y (N%)      X/Y (N%)      PASS|FAIL|REGRESSED
Baseline delta: <vs last run>
```
Files in this package (2)
  • SKILL.md 1 KB
  • agents/openai.yaml 1 KB

Versions

RepositoryScoreLicence
This page · prashantxo/codeforge100MIT
relai-ai/agent-eval-loop100Apache-2.0
jisuzzzz/haechi100MIT
alirezarezvani/claude-skills100MIT
ai-analyst-lab/ai-analyst100MIT
ai-analyst-lab/ai-analyst-plugin100MIT
pspdfkit-labs/agentic-usability100Apache-2.0
netanel-abergel/pa-skills100MIT
Kanevry/session-orchestrator98MIT

Database snapshot: 13.11.2026 · package version 5ab1455d02d2 (SHA-256 digest of the entire package)

Downloads in the last 30 days: 0 · ranking

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