Analyzes test coverage to identify and suggest missing edge case scenarios.

Install

mkdir -p .claude/skills/edge-cases-sprocketlab && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/12504" && unzip -o skill.zip -d .claude/skills/edge-cases-sprocketlab && rm skill.zip

Installs to .claude/skills/edge-cases-sprocketlab

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Analyze checkpoint tests and suggest missing edge cases. Use after writing tests or when reviewing test coverage. Invoke with /edge-cases <problem> <checkpoint>.
161 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • Analyze checkpoint specifications
  • Identify missing edge cases in tests
  • Implement edge-case tests with assertions
  • Cross-reference spec requirements with existing tests
  • Validate JSON and file references

How it works

This skill analyzes a checkpoint's specification and existing tests to identify gaps and implement missing edge cases, ensuring complete test coverage.

Inputs & outputs

You give it
A problem and checkpoint identifier
You get back
Appended edge-case tests to `test_checkpoint_N.py` and a validation report

When to use edge-cases

  • Identify missing tests
  • Increase coverage
  • Add edge case assertions

About this skill

Edge Case Analyzer

Analyze a checkpoint's spec and existing tests to identify and add missing edge cases.

Usage: /edge-cases execution_server checkpoint_2

Workflow

  1. Read the spec - Understand all requirements, constraints, error conditions
  2. Read existing tests - See what's already covered
  3. Identify gaps - Find missing edge cases
  4. Implement edge-case tests - Add fully implemented tests with real assertions

Step 1: Gather Context

Read these files for the specified problem/checkpoint:

problems/{problem}/checkpoint_N.md
problems/{problem}/tests/conftest.py
problems/{problem}/tests/test_checkpoint_N.py

Step 2: Analyze for Gaps

For each requirement in the spec, ask:

  1. What happens with empty/null input?
  2. What happens at boundary values (0, -1, max, min)?
  3. What happens with malformed input?
  4. What happens with missing required fields?
  5. What happens with unexpected types?
  6. Are there race conditions or state edge cases?
  7. Are there format edge cases (unicode, special chars)?
    • Use \uXXXX escapes to keep source files ASCII when needed.

Cross-reference with existing tests:

  • Which spec requirements have tests?
  • Which error conditions are tested?
  • Which boundary conditions are tested?
  • What did the spec mention that tests don't cover?

See references/edge-case-categories.md for the category checklist and references/patterns.md for problem-type patterns.


Important: Avoid Ambiguous Cases

Only add edge cases where the spec is clear about expected behavior.

If the spec is ambiguous or there are multiple valid interpretations:

  • Don't add a test - it's not a valid edge case
  • The spec should define the expected behavior, not the tests
  • Tests should verify spec compliance, not invent requirements

Good edge case: Spec says "return error for negative values" → test with -1 Bad edge case: Spec doesn't mention negatives → we don't know what should happen

Ask yourself: "Can I point to the spec line that defines this behavior?"

  • Yes → Valid edge case
  • No → Skip it or note the spec ambiguity

Step 3: Implement Edge Case Tests

Append to test_checkpoint_N.py with fully implemented tests. Do not add TODOs, pytest.fail, or placeholder assertions. If you cannot implement an edge case from the spec, skip it or ask for clarification instead of adding incomplete tests.

Keep tests readable with tiny helper functions for recurring patterns (CLI runs, input setup, HTTP JSON requests). Prefer local helpers in the test module unless the helper is shared across multiple test files. See references/helper-patterns.md for helper ideas and references/example-patterns.md for CLI/HTTP layouts.

Do not leave placeholder docstrings. Either quote the spec line or remove the docstring entirely.


Markers to Use

All edge cases use @pytest.mark.functionality.

Edge cases are additional coverage beyond the core tests - they should not block a passing submission. Core tests cover the main spec requirements; edge cases catch less common scenarios.


After Adding Tests

  1. ALWAYS Run eval-snapshot to verify:
    slop-code --quiet eval-snapshot problems/{problem}/solutions/checkpoint_N \
        -p {problem} -o /tmp/eval -c N \
        -e configs/environments/docker-python3.12-uv.yaml --json
    

Reference

When not to use it

  • When the spec is ambiguous about expected behavior
  • When the goal is to invent new requirements through tests

Limitations

  • Only adds edge cases where the spec is clear
  • Does not add tests for ambiguous spec behavior
  • Requires `pytest.mark.functionality` for all edge cases

How it compares

This workflow systematically identifies and adds edge cases based on explicit spec requirements, unlike ad-hoc test creation.

Compared to similar skills

edge-cases side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
edge-cases (this skill)07moReviewIntermediate
python-testing-patterns772moReviewIntermediate
chrome-devtools417moReviewIntermediate
bats97moReviewIntermediate

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