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 skills add aAAaqwq/AGI-Super-Team --skill agent-testergit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote 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/aaaaqwq/agi-super-team/agent-tester)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/agent-tester"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/agent-tester/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/agent-tester"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/agent-tester.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00000 | $0.00856 |
| Opus 5 | $0.00000 | $0.00428 |
| Sonnet 5 | $0.00000 | $0.00171 |
| Haiku 4.5 | $0.00000 | $0.00086 |
Grade A, and why
agent-tester 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 10d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
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
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.
- 10d ago First seen · 148 lines · 0 tokens per session scan A 94ef7d0b9e06
agent-tester is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 856 tokens. 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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