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 skills add hidai25/eval-view --skill generate-testsgit clone --depth 1 https://github.com/hidai25/eval-viewWrote 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.
[](https://agentmods.dev/skills/hidai25/eval-view/generate-tests)<a href="https://agentmods.dev/skills/hidai25/eval-view/generate-tests"><img src="https://agentmods.dev/badge/skills/hidai25/eval-view/generate-tests/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hidai25/eval-view/generate-tests"><img src="https://agentmods.dev/badge/skills/hidai25/eval-view/generate-tests.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Excessive Agency · line 64 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
- medium Agent Snooping · line 26 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 27 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.00627 |
| Opus 5.5 | $0.00013 | $0.00251 |
| Sonnet 5.5 | $0.00006 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00063 |
Grade A, and why
generate-tests 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 1mo 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Tests
Use this skill when the user wants to create test cases for their AI agent or skill without writing YAML by hand.
Four approaches
1. Generate tests from a SKILL.md file
Use the generate_skill_tests MCP tool to auto-generate a test suite from a skill definition. This reads the SKILL.md and produces YAML test cases covering explicit triggers, implicit triggers, contextual triggers, and negative cases.
Steps:
- Ask the user which SKILL.md to generate tests for (or detect it from context).
- Call
generate_skill_testswith:skill_path: path to the SKILL.md fileoutput_path(optional): where to save the generated YAMLcount(optional): number of test cases (default: 10)
- After generation, offer to run the tests with
run_skill_test.
CLI equivalent:
evalview skill generate-tests .claude/skills/my-skill/SKILL.md --auto
evalview skill generate-tests .claude/skills/my-skill/SKILL.md -c 20 -o tests/my-skill-tests.yaml
2. Create individual test cases manually
Use the create_test MCP tool to create a single test YAML file from a description.
Steps:
- Gather from the user: test name, query, expected tools, forbidden tools, expected output keywords, and minimum score.
- Call
create_testwith the parameters. - After creating the test, call
run_snapshotto establish the golden baseline.
3. Capture real interactions
Use the CLI evalview capture command to proxy real agent traffic and save interactions as test YAMLs automatically. This records the query, output, and tool calls from live usage.
CLI equivalent:
evalview capture --agent http://localhost:8080/execute --output-dir tests/test-cases
evalview capture --multi-turn # saves all turns as one multi-turn conversation test
4. Validate a skill before testing
Use validate_skill to check a SKILL.md for correct structure and completeness before generating tests from it.
Running generated tests
After generating tests, execute them with run_skill_test:
test_file: path to the generated YAMLno_rubric: truefor fast deterministic-only checks (no LLM cost)verbose: truefor detailed output on all tests
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.
- 1mo ago First seen · 66 lines · 32 tokens per session scan A 6eab594cec94
generate-tests is a skill published in the GitHub repository hidai25/eval-view (140 stars, last pushed 5d ago), licensed Apache-2.0. It adds 32 tokens to every session and 627 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
create-custom-grader
Use when converting an existing benchmark, rubric, verifier, task YAML/JSON, or domain check into SkillEvaluator BYOG/BYOT custom evaluation.
testing-llm
LLM and AI testing patterns — mock responses, evaluation with DeepEval/RAGAS, structured output validation, and agentic test patterns (generator, healer, planner). Use when testing AI features, validating LLM outputs, or building evaluation pipelines.
nasde-benchmark-runner
Run coding agent benchmarks and verify results with nasde. Use this skill when the user wants to: Run a benchmark (all tasks, single task, specific variant) Re-run assessment evaluation on existing trial results Check or verify results in Opik (traces, feedback scores, experiments) Troubleshoot a failed benchmark run…
nasde-benchmark-calibration
Calibrate assessment rubrics by reviewing agent work in GitHub/GitLab PRs and feeding human comments back into the rubric. Use this skill when the user wants to: Calibrate, tune, or sanity-check assessment criteria / dimensions of a benchmark Review trial diffs alongside the LLM-as-a-Judge scores in a PR/MR…
nasde-benchmark-creator
Create coding agent benchmarks for evaluation with nasde. Use this skill when the user wants to: Create a new benchmark project (set of tasks for evaluating coding agents) Add tasks to an existing benchmark Create or modify agent variants (configurations that control agent behavior) Set up assessment dimensions and…
nasde-benchmark-from-public-repos
Build diverse benchmark task suites from public GitHub repositories for testing universal skills. Use this skill when the user wants to: Create a benchmark that spans multiple public repositories and languages Test a universal skill (refactoring, test writing, code review, etc.) across diverse codebases Curate a…