Purpose

Build test infrastructure for a skill: trigger tests (positive and negative JSONL cases) and output-format tests. Enables repeatable evaluation during development and refinement.

When to use

• User says "create tests for this skill", "set up evals", "build a test harness"
• New skill needs test coverage
• Skill lacks an evals/ directory or test fixtures
• Skill refinement requires regression tests

When NOT to use

• Running existing tests →

  skill-evaluation

• Comparing skill variants →

  skill-benchmarking

• Tests exist and need minor edits → edit directly

Procedure

Step 1 — Analyze the target skill

Read the target SKILL.md and extract:

• Trigger signals from the

  description

  field
• Positive cases from "When to use" section
• Negative cases from "When NOT to use" section
• Expected output format from output contract
• Quality criteria from procedure steps

Step 2 — Create trigger-positive.jsonl

File:

evals/trigger-positive.jsonl

Each line is a JSON object for a prompt that SHOULD activate the skill. Include 8–15 cases covering core use cases, edge cases, and paraphrasings.

Positive cases must cover these categories:

• (a) Exact match: Prompts that directly mirror a "When to use" bullet
• (b) Paraphrase: Same intent expressed with different vocabulary
• (c) Indirect: Requests that imply the skill's purpose without naming it (e.g., describing a problem the skill solves)
• (d) Multi-step: Requests where this skill is one component of a larger task

Aim for at least 2 cases per category. If a category produces fewer than 2 natural cases, the skill's trigger surface may be too narrow — note this in the README.

{"prompt": "Create a new skill for handling PDF extraction", "expected": "trigger", "category": "core", "notes": "Direct request matching primary use case"}
{"prompt": "I need a reusable procedure for database migrations", "expected": "trigger", "category": "indirect", "notes": "Implicit skill creation — repeated task pattern"}
{"prompt": "Can you make a skill that handles our deploy workflow?", "expected": "trigger", "category": "paraphrase", "notes": "Casual phrasing"}
{"prompt": "Package this workflow as a skill for the team", "expected": "trigger", "category": "edge", "notes": "Packaging intent implies creation first"}

prompt

expected

"trigger"

category

core

indirect

paraphrase

edge

notes

Step 3 — Create trigger-negative.jsonl

File:

evals/trigger-negative.jsonl

Each line is a JSON object for a prompt that should NOT activate the skill. Include 8–15 cases covering adjacent skills, out-of-scope tasks, and common confusion.

Negative cases must cover these categories:

• (a) Anti-match: Prompts that directly mirror a "When NOT to use" bullet
• (b) Near-miss: Tasks from adjacent skills that share vocabulary (e.g., "evaluate" vs "build evaluation for")
• (c) Similar vocabulary, different intent: Requests using words like "test" or "eval" that mean something else in context
• (d) Overly broad: Vague requests that superficially match but shouldn't trigger (e.g., "improve this skill" — too broad for a test harness)

Minimum distribution across all trigger cases: 60% positive, 30% negative, 10% edge-case (ambiguous intent where

expected

"trigger"

"no_trigger"

notes

{"prompt": "Fix the trigger description on this skill", "expected": "no_trigger", "better_skill": "skill-trigger-optimization", "notes": "Trigger fix, not test creation"}
{"prompt": "Run the existing eval suite", "expected": "no_trigger", "better_skill": "skill-evaluation", "notes": "Running tests, not building them"}
{"prompt": "Compare these two skill variants", "expected": "no_trigger", "better_skill": "skill-benchmarking", "notes": "Benchmarking, not test infrastructure"}
{"prompt": "Write a Python function to parse JSON", "expected": "no_trigger", "better_skill": null, "notes": "General coding, not skill engineering"}

prompt

expected

"no_trigger"

better_skill

null

notes

Step 4 — Create behavior tests

File:

evals/behavior.jsonl

Each line defines a prompt with expected output characteristics.

Output quality assertions should check:

• (a) Required sections present: Every section named in the skill's output contract must appear
• (b) No hallucinated sections: Flag any output section not specified in the output contract
• (c) Output length within range: Set

  min_output_lines

  based on the skill's complexity. A skill with 3 procedure steps shouldn't produce 200-line output.
• (d) Concrete vs vague language: Flag if >30% of output sentences use hedge words ("consider", "may want to", "could potentially", "it might be useful to"). Skills should produce decisions, not suggestions.

{"prompt": "Create trigger tests for skill-authoring", "expected_sections": ["trigger-positive", "trigger-negative"], "required_patterns": ["\"expected\": \"trigger\"", "\"expected\": \"no_trigger\""], "forbidden_patterns": ["TODO", "placeholder", "consider adding"], "min_output_lines": 15, "notes": "Must produce both positive and negative trigger files"}
{"prompt": "Build a full test harness for the pdf-extraction skill", "expected_sections": ["trigger-positive", "trigger-negative", "behavior"], "required_patterns": ["\"better_skill\"", "\"expected_sections\""], "forbidden_patterns": ["may want to", "could potentially"], "min_output_lines": 20, "notes": "Full harness must include all three eval files plus README"}

Step 5 — Create test fixtures (if needed)

Directory:

evals/fixtures/

Only create fixtures when the skill processes files or external data: sample inputs, mock data for deterministic testing, expected output examples.

Step 6 — Create evals README

File:

evals/README.md

# Eval Suite for [skill-name]

## Files
| File | Purpose | Case Count |
|------|---------|------------|
| trigger-positive.jsonl | Prompts that SHOULD trigger | N |
| trigger-negative.jsonl | Prompts that should NOT trigger | N |
| behavior.jsonl | Output format/content validation | N |

## Running
- Trigger tests: Feed each prompt to router, verify trigger/no_trigger matches expected
- Output tests: Run skill on each prompt, verify files/patterns/counts

## Adding Cases
Append new JSON lines to the appropriate .jsonl file. Follow the field schema:
- trigger-positive: prompt, expected ("trigger"), category, notes
- trigger-negative: prompt, expected ("no_trigger"), better_skill, notes

Step 7 — Verify the test suite

After creating all eval files, verify they are well-formed and parseable:

./scripts/run-evals.sh --dry-run <skill-name>

This validates JSONL syntax, lists all test cases, and confirms the eval runner can parse them. Fix any errors before delivering the test suite.

Output contract

evals/
├── README.md              # How to run and extend tests
├── trigger-positive.jsonl # 8–15 should-trigger cases
├── trigger-negative.jsonl # 8–15 should-not-trigger cases
├── behavior.jsonl         # Output format/content validation
└── fixtures/              # Optional test data

All JSONL files use one JSON object per line, newline-delimited.

Failure handling

• No clear triggers in description: Cannot write trigger tests — flag for

  skill-trigger-optimization

  first
• Output format undefined: Cannot write output tests — flag for

  skill-improver

  to add output contract
• Too few distinct trigger phrases: Minimum 5 positive, 5 negative; if the skill is too narrow, consult

  skill-catalog-curation

  to assess whether it should be merged
• Skill too complex for single harness: Split into sub-capabilities with separate JSONL files per capability
• No comparable baseline: Skip baseline comparison; focus on trigger accuracy and output format compliance

Next steps

After building the test harness:

• Run the tests →

  skill-evaluation

• Compare variants →

  skill-benchmarking