Agent Tester
SkillAI & modelsTest agent: dry-run, unit, integration, compatibility
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Agent Tester skill
What this skill tells your AI
The instructions your AI receives, as published by aaaaqwq/agi-super-team in skills/agent-tester/SKILL.md and read by ahel’s review.
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:
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:
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!
- Back up data that the agent modifies:
cp [target.csv] [target.csv.backup]
-
Run the agent once on real data
-
Check output:
- Data was written correctly
- Format matches schema.yaml
- Nothing broke
- Git commit was created (if needed)
-
If something is wrong -- rollback:
cp [target.csv.backup] [target.csv]
Step 5: Compatibility test
Check that the new agent does not conflict with existing ones:
## 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:
# 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 specagent-builder— builds the agentchange-review— validates CRM/PM changes
Signals
- GitHub stars
- 92
- Forks
- 23
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
agent-tester- Source
- github.com/aaaaqwq/agi-super-team