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.
npx agentmods add skills/agricidaniel/skill-forge/skill-forge-evalnpx skills add AgriciDaniel/skill-forge --skill skill-forge-evalgit clone --depth 1 https://github.com/AgriciDaniel/skill-forgeWhat 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 | $0.00095 | $0.01697 |
| Opus 5 | $0.00048 | $0.00848 |
| Sonnet 5 | $0.00019 | $0.00339 |
| Haiku 4.5 | $0.00010 | $0.00170 |
Grade A, and why
skill-forge-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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Evaluation Pipeline
Run structured evaluations against Claude Code skills to verify triggering, correctness, and quality using a multi-agent pipeline.
Process
Step 1: Define Eval Set
Accept eval definitions from:
- Path to eval set JSON:
evals/evals.jsonor user-specified file - Inline prompts: User provides eval queries directly
- Auto-generated: Generate from skill description (see Step 1b)
Eval set JSON schema:
{
"skill_name": "my-skill",
"skill_path": "./my-skill",
"evals": [
{
"eval_id": 0,
"eval_name": "descriptive-name",
"prompt": "The user's task prompt",
"input_files": [],
"assertions": [
{
"name": "output-has-score",
"check": "Output contains a numeric score between 0-100",
"weight": 1.0
}
],
"should_trigger": true
}
]
}
Step 1b: Auto-Generate Eval Set
If no eval set exists, generate one:
- Read the skill's SKILL.md description and instructions
- Run
python scripts/generate_eval_set.py <skill-path>to produce a starter set - Present the generated set to the user for review and editing
- User approves or modifies before proceeding
Step 2: Set Up Workspace
Create the eval workspace outside the skill directory to avoid confusing eval artifacts with skill files. Use a sibling directory or a dedicated location:
eval-workspace/
iteration-1/
eval-0/
eval_metadata.json # Assertions and config for this eval
with_skill/
outputs/ # Skill execution outputs
timing.json # Token count + duration
grading.json # Assertion results + evidence
baseline/
outputs/
timing.json
grading.json
eval-1/
eval_metadata.json
with_skill/
outputs/
timing.json
grading.json
baseline/
outputs/
timing.json
grading.json
benchmark.json # Aggregated metrics
benchmark.md # Human-readable report
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.
- 2d ago First seen · 233 lines · 95 tokens per session scan A 8f124e2ad95d
skill-forge-eval is a skill published in the GitHub repository AgriciDaniel/skill-forge (166 stars, last pushed 4mo ago), licensed MIT. It adds 95 tokens to every session and 1,697 once invoked, about $0.0005 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 2026-08-30.
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