Best use case
agent-tester is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Test agent: dry-run, unit, integration, compatibility
Teams using agent-tester should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/agent-tester/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent-tester Compares
| Feature / Agent | agent-tester | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Test agent: dry-run, unit, integration, compatibility
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Agent Tester > Tests a built agent: dry-run, unit tests, integration, compatibility with other agents. ## When to use - After Agent Builder has finished - "test agent X" - "check agent compatibility" ## Input - Agent from `$AGENTS_PATH/[name]/` - Spec from `$AGENTS_PATH/specs/[name].spec.md` ## How to execute ### Step 1: Static analysis Check the agent code: - [ ] File exists and runs without syntax errors - [ ] All imports resolve - [ ] Config file is valid - [ ] Paths in config exist - [ ] Credentials are accessible - [ ] Dry-run mode is implemented ### Step 2: Dry-run test Run the agent with `--dry-run`: ```bash python3 $AGENTS_PATH/[name]/[name]_agent.py --dry-run ``` Check: - [ ] Agent starts without errors - [ ] Logs are clear - [ ] Shows what it WOULD do (without real side effects) - [ ] Execution time is reasonable ### Step 3: Unit tests Run tests: ```bash python3 -m pytest $AGENTS_PATH/[name]/test_[name].py -v ``` Minimum tests: - [ ] Input parsing works - [ ] Business logic is correct on test data - [ ] Error handling works (bad input, missing files, API timeout) - [ ] Output format is correct ### Step 4: Integration test (one run on real data) **WARNING: only with human approval!** 1. Back up data that the agent modifies: ```bash cp [target.csv] [target.csv.backup] ``` 2. Run the agent once on real data 3. Check output: - [ ] Data was written correctly - [ ] Format matches schema.yaml - [ ] Nothing broke - [ ] Git commit was created (if needed) 4. If something is wrong -- rollback: ```bash cp [target.csv.backup] [target.csv] ``` ### Step 5: Compatibility test Check that the new agent does not conflict with existing ones: ```markdown ## Compatibility Matrix | Agent | Shared Files | Potential Conflict | Status | |-------|-------------|-------------------|--------| | Email Pipeline | activities.csv | Write conflict | ? | | [other agents] | ... | ... | ? | ``` Specific checks: - [ ] **File locks**: can two agents write to the same CSV simultaneously - [ ] **Data consistency**: does the agent overwrite another agent's data - [ ] **ID generation**: do IDs conflict (person_id, activity_id, etc.) - [ ] **Schedule overlap**: do agents run at the same time - [ ] **Git conflicts**: does auto-commit create merge conflicts ### Step 6: Report Create a test report file: ``` $AGENTS_PATH/specs/[name].test-report.md ``` **Report structure:** ```markdown # Test Report: [Agent Name] ## Date: YYYY-MM-DD ## Tester: Process Analyst Agent ## Results | Test | Status | Notes | |------|--------|-------| | Static analysis | PASS/FAIL | | | Dry-run | PASS/FAIL | | | Unit tests | PASS/FAIL | X/Y passed | | Integration | PASS/FAIL | | | Compatibility | PASS/FAIL | | ## Issues Found 1. [Issue description + severity] ## Recommendation - [ ] READY for production - [ ] NEEDS FIXES (list what) - [ ] BLOCKED (list why) ``` ## Output - Test report in `$AGENTS_PATH/specs/[name].test-report.md` - PASS/FAIL verdict - List of issues if any ## Related skills - `process-analyst` — creates the spec - `agent-builder` — builds the agent - `change-review` — validates CRM/PM changes
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