create-skill-eval

create-skill-eval is a skill for Claude Code, Codex from astra-sh/qvr. It costs 129 tokens per session (2,534 once invoked), scanned A, original, MIT.

A method for creating a fixed evaluation harness for one coding-agent skill. The harness contains test scenarios, sample data, grading rules, and a deterministic evaluator.

In plain words
What is it for?
Freezing tests and scoring logic for a specific skill, such as checking SQL results, exact strings, or whether a code change builds and passes tests.
Why use it?
It makes the skill's expected behavior measurable and repeatable instead of relying on informal judgments.

Skill for Claude CodeCodex

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 skills/astra-sh/qvr/create-skill-eval
Any agent
npx skills add astra-sh/qvr --skill create-skill-eval
Clone the repo
git clone --depth 1 https://github.com/astra-sh/qvr

Made for: Claude Code, Codex.

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 create-skill-eval

README.md
[![agentmods](https://agentmods.dev/badge/skills/astra-sh/qvr/create-skill-eval.svg)](https://agentmods.dev/skills/astra-sh/qvr/create-skill-eval)
Your own site
<a href="https://agentmods.dev/skills/astra-sh/qvr/create-skill-eval"><img src="https://agentmods.dev/badge/skills/astra-sh/qvr/create-skill-eval.svg" alt="Measured on agentmods" height="20"></a>
Per session 129 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,534 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original 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 $0.00129 $0.02534
Opus 5 $0.00064 $0.01267
Sonnet 5 $0.00026 $0.00507
Haiku 4.5 $0.00013 $0.00253

Measured 5d ago against content hash 1d7d4450d2fb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

create-skill-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 5d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/validate-harness.py, templates/eval.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/create-skill-eval/SKILL.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

create-skill-eval

Build the graded harness for one inner skill and freeze it into that skill's eval/ directory. This is step "instrument the baseline" factored out of the optimizer: the how to grade THIS skill lives here and ships with the skill; the how to run the loop lives in optimize-skill-loop and is skill-agnostic.

  • You produce a conformant eval/ dir (see references/eval-contract.md).
  • optimize-skill-loop consumes it read-only and never edits it.

The eval/ you freeze is the two halves of the loop's contract made concrete: it rides the skill's qvr version (so the loop can switch to a content version before each cohort), and its eval.py + rubric.yaml are what turn each captured qvr session → metrics ∈[0,1]. qvr is the loop's inner ledger — it owns the sessions, the cost, and the per-version identity; your harness only supplies the grading. You never plumb session ids or cost here; you author what correct means for this skill and hand it off frozen.

The eval is the inner skill's own asset. Grading text2sql (run the SQL, diff the rows), slugify (string match), and a codemod (build + test) have nothing in common — that difference belongs in the skill's eval/, authored here, not baked into the generic optimizer.

The deliverable: a conformant eval/ (the contract)

Everything you write must satisfy references/eval-contract.md — that's the seam the optimizer relies on. The frozen dir:

<skill>/eval/
  HARNESS.md          # manifest: metrics, axes, agents/N/models, exit, fixtures
  scenarios.jsonl     # frozen cases {id, input, expected?}
  eval.py             # deterministic grader CLI (--metric <id>, --explain)
  rubric.yaml         # frozen LLM-judge dimensions/weights/anchors
  <fixtures/builders> # whatever eval.py needs

Once frozen, the whole dir is byte-stable for the loop: git diff <baseline> <candidate> -- '*/eval/*' is empty forever after.

0. Prereq

Requires python3 on PATH — the grader you author (eval.py), its fixture builders, and scripts/validate-harness.py all use it (stdlib only, no pip install). PyYAML is optional: the validator falls back to a minimal manifest parser when it's absent.

Read the full file on GitHub · 207 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 5d ago First seen · 207 lines · 129 tokens per session scan A 1d7d4450d2fb

Subscribe to this mod's changes

create-skill-eval is a skill published in the GitHub repository astra-sh/qvr (23 stars, last pushed 2mo ago), licensed MIT. It adds 129 tokens to every session and 2,534 once invoked, about $0.0006 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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