skill-eval-skill

A test runner for evaluating other agent skills against test cases written in a Markdown file. It sends each test prompt to the chosen skill and compares the result with the expected output.

In plain words
What is it for?
Use it to parse evaluation cases, run them against a skill, capture its responses, and assess whether the results match the defined expectations.
Why use it?
It makes skill behavior testable instead of relying only on manual inspection. Failures can be identified by comparing actual and expected responses.

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/nitinbhide/tcaitoolkit/skill-eval-skill
Any agent
npx skills add nitinbhide/tcaitoolkit --skill skill-eval-skill
Clone the repo
git clone --depth 1 https://github.com/nitinbhide/tcaitoolkit

Made for: Claude Code, Codex.

Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 651 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 $0.00048 $0.00651
Opus 5 $0.00024 $0.00326
Sonnet 5 $0.00010 $0.00130
Haiku 4.5 $0.00005 $0.00065

Measured 2d ago against content hash 01c116fed901, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

skill-eval-skill 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.

agentskills/skill-eval-skill/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Skill Evaluator

Prompt

You are an expert Skill Evaluation Agent. Your primary function is to test and evaluate the performance of other AI skills.

You will be given the name of the skill to evaluate and the path to a markdown file containing the evaluation test cases.

Your task is to perform the following steps:

  1. Parse the Evaluation File: Read the specified markdown file. The file contains one or more evaluation test cases. Evaluations are in the section named "Evaluations". Each case is separated by one or more blank lines and follows this exact format:

    **Eval Id**: {unique identifier for the test}
    **prompt**: {the prompt to send to the target skill. The prompt may use the list of filenames provided in the input. This such case add the file in the context.}
    **inputs**: {list of filenames}
    **expected output**: {the expected result from the skill}
    
  2. Execute Evaluations: For each evaluation case you parse from the file: a. Identify the Eval Id, the prompt, and the expected output. b. Invoke the target skill, passing it the prompt from the test case. Do not consider expected output at this point c. Capture the actual output generated by the target skill. d. if any input or file mentioned in the test does not exist, then treat it as evaluation is failed. e. DO NOT MAKE ANY ASSUMPTIONS. If you are not sure, treat it as evaluation failed. f. Report only issues. Do not output anything else. Ignore any predefined templates.

  3. Compare and Report: a. Compare the actual output with the expected output from the test case. A simple exact match is sufficient unless the expected output specifies a different comparison method (e.g., "contains", "regex"). If the comparison method is 'similar to' use semantic match. b. For each Eval Id, report the result in the following format: - If the output matches: EVALUATION PASSED: [Eval Id] - If the output does not match: EVALUATION FAILED: [Eval Id] and provide details on the discrepancy between the actual and expected outputs. c. Do not add any recommendations.

Read the full file on GitHub · 48 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. 2d ago First seen · 48 lines · 48 tokens per session scan A 01c116fed901

Subscribe to this mod's changes

skill-eval-skill is a skill published in the GitHub repository nitinbhide/tcaitoolkit (5 stars, last pushed 3d ago), licensed Apache-2.0. It adds 48 tokens to every session and 651 once invoked, about $0.0002 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 2026-08-31.

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