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 agentmods add skills/humanerd-drew/opencode-drewgent/qa-scenario-gennpx skills add humanerd-drew/opencode-drewgent --skill qa-scenario-gengit clone --depth 1 https://github.com/humanerd-drew/opencode-drewgentWrote 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/humanerd-drew/opencode-drewgent/qa-scenario-gen)<a href="https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/qa-scenario-gen"><img src="https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/qa-scenario-gen.svg" alt="Measured on agentmods" 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 | $0.00009 | $0.00526 |
| Opus 5 | $0.00005 | $0.00263 |
| Sonnet 5 | $0.00002 | $0.00105 |
| Haiku 4.5 | $0.00001 | $0.00053 |
Grade A, and why
qa-scenario-gen 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 5d 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.
What it actually says
qa-scenario-gen — Test Scenario Generator
Purpose
Analyzes user requirements and generates:
- Structured acceptance criteria for
contract.json - Test scenarios for micro-QA verification
- Edge cases and boundary conditions
How It Works
Parses user task description to extract:
- Functional requirements → acceptance criteria
- Technical components → test scenarios
- Error conditions → edge case tests
- Performance needs → non-functional tests
Usage
skill: qa-scenario-gen
task_description: "Build a REST API that does X"
output_format: contract_json | scenarios | checklist
Output Structure
contract.json format
{
"task_id": "auto-generated",
"acceptance_criteria": [
{
"id": "AC-001",
"description": "API endpoint returns correct status code",
"priority": "P0",
"test_method": "automated",
"verified": false
}
]
}
Test Scenarios
Scenario 1: Happy Path
Given: valid input
When: API called
Then: returns 200 with expected data
Scenario 2: Invalid Input
Given: malformed input
When: API called
Then: returns 400 with error message
Hugh Kim's Approach
From Loopy-Era Harness:
- CONTRACT-FIRST: Write contract before implementation
- PHASE 2.5: 시나리오 확정 → 구현 → micro-QA → full-QA
- Scenarios become the micro-QA checklist
Integration
- Output feeds into
QAEvidenceManager.create_contract() - Scenarios map to
micro-qa_*.jsonfiles - Edge cases become acceptance criteria with P0 priority
Related
- [[@action/skills/SKILL-INDEX]]
- [[@action/skills/qa/DESCRIPTION]]
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.
- 5d ago First seen · 89 lines · 9 tokens per session scan A ae0fda3eb8dd
qa-scenario-gen is a skill published in the GitHub repository humanerd-drew/opencode-drewgent (2 stars, last pushed 1mo ago), licensed MIT. It adds 9 tokens to every session and 526 once invoked, about $0.0000 per session on Opus 5. 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 2026-08-31.
Other skills, from other repositories
qa-acceptance
Produce QA acceptance criteria and a manual validation plan for a feature change — golden path, edge cases, error states, performance limits, and explicit pass/fail evidence.
agent-qa-result-triage
Triage failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next steps.
project-brainstorming
Guides project ideation via Socratic questioning to produce a validated brief. Use before specification when requirements are unclear.
project-specification
Transforms project briefs into testable specifications with user stories and acceptance criteria. Use after brainstorming, before planning.
gsd:new-project
Initialize a new project with deep context gathering and PROJECT.md. Creates project structure, requirements, roadmap, and state.
gsd-roadmapper
Creates project roadmaps with phase breakdown, requirement mapping, success criteria derivation, and coverage validation. Spawned by /gsd:new-project orchestrator.