Borrowing it
Nothing to install: this file belongs to Artesiana/agent2. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Artesiana/agent2/main/.agents/skills/agent-qa/SKILL.mdgit clone --depth 1 https://github.com/Artesiana/agent2Wrote 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/artesiana/agent2/agent-qa)<a href="https://agentmods.dev/skills/artesiana/agent2/agent-qa"><img src="https://agentmods.dev/badge/skills/artesiana/agent2/agent-qa/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/artesiana/agent2/agent-qa"><img src="https://agentmods.dev/badge/skills/artesiana/agent2/agent-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00070 | $0.01061 |
| Opus 5.5 | $0.00028 | $0.00424 |
| Sonnet 5.5 | $0.00014 | $0.00212 |
| Haiku 4.5 | $0.00007 | $0.00106 |
Grade A, and why
agent-qa scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "http://localhost:$AGENT_PORT/health" 2>/dev/null && echo "ALREADY_RUNNING" || echo "NEEDS_START" How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent QA
End-to-end testing for a deployed or locally running Agent2 agent.
When to Use
- After generating a new agent with
/brain-cloneor/creating-agents - After changing an agent's prompt, tools, or schema
- Before shipping an agent to production
- When debugging unexpected agent behavior
Workflow
Step 1: Identify the agent
Ask which agent to test if not obvious from context:
ls agents/*/config.yaml 2>/dev/null | sed 's|agents/||;s|/config.yaml||'
Step 2: Load test cases
Check for existing eval datasets:
AGENT_NAME="<agent-name>"
EVAL_FILE="tests/promptfoo/$AGENT_NAME/dataset.json"
if [ -f "$EVAL_FILE" ]; then
echo "EVAL_FOUND: $EVAL_FILE"
cat "$EVAL_FILE"
else
echo "NO_EVAL_DATASET"
fi
If NO_EVAL_DATASET: generate test cases from the agent's example cases in
config.yaml and the prompt in agent.py. Create at least 3 cases:
- A case that should return the primary complete outcome
- An empty/incomplete case that should trigger needs_clarification
- A case with a defect that should trigger rejected (if applicable)
Step 3: Start the agent
# Check if already running
AGENT_PORT=$(grep "port:" "agents/$AGENT_NAME/config.yaml" | awk '{print $2}')
curl -s "http://localhost:$AGENT_PORT/health" 2>/dev/null && echo "ALREADY_RUNNING" || echo "NEEDS_START"
If NEEDS_START:
uv run agent2 serve "$AGENT_NAME" &
AGENT_PID=$!
sleep 3
curl -s "http://localhost:$AGENT_PORT/health"
Step 4: Run test cases
For each test case, send a real POST /tasks request:
curl -s -X POST "http://localhost:$AGENT_PORT/tasks?mode=sync" \
-H "Authorization: Bearer dev-token-change-me" \
-H "Content-Type: application/json" \
-d '{"input": <test-case-input>}'
For each response, validate:
- HTTP status is 200
- Response contains
"status": "completed" resultis present and contains the expected schema fieldsresult.statusmatches expected outcome (if specified in test case)result.confidenceis a number between 0 and 1result.reasoningis non-emptyresult.review_stepsis a non-empty list- Schema consistency: no contradictory fields (e.g., complete + rejection_reason)
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.
- 2mo ago First seen · 141 lines · 70 tokens per session scan A e3ad95cb9e91
agent-qa is a skill published in the GitHub repository Artesiana/agent2 (37 stars, last pushed 6mo ago), licensed MIT. It adds 70 tokens to every session and 1,061 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
agent-qa compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| agent-qaArtesiana/agent2 | Skill | 37 | 6mo ago | MIT | A | 70 | Claude Code, Codex |
| 测试基础设施jianchen08/Agent-os-open | Skill | 7 | 29d ago | Apache-2.0 | A | 35 | Claude Code, Codex |
| test-generationsarveshtalele/mcp-skills-registry | Skill | 3 | 1mo ago | MIT | A | 51 | Claude Code, Codex |
| playwright-skilljianchen08/Agent-os-open | Skill | 7 | 29d ago | Apache-2.0 | A | 139 | Claude Code, Codex |
| dogfoodNousResearch/hermes-agent | Skill | 261k | today | MIT | A | 18 | Claude Code, Codex |
| tdd-workflowaffaan-m/ECC | Skill | 298k | 4d ago | MIT | A | 43 | Claude Code, Codex |
| e2e-testingaffaan-m/ECC | Skill | 298k | 4d ago | MIT | A | 53 | Claude Code, Codex |