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/hidai25/eval-view/generate-testsnpx 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.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00032 | $0.00627 |
| Opus 5 | $0.00016 | $0.00313 |
| Sonnet 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 4d 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.
- 4d 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 (133 stars, last pushed 11d ago), licensed Apache-2.0. It adds 32 tokens to every session and 627 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 2026-08-30.
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