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 commands/cloudai-x/opencode-workflow/test-designgit clone --depth 1 https://github.com/CloudAI-X/opencode-workflowWhat 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 | $0.00009 | $0.00987 |
| Opus 5 | $0.00005 | $0.00494 |
| Sonnet 5 | $0.00002 | $0.00197 |
| Haiku 4.5 | $0.00001 | $0.00099 |
Grade A, and why
test-design 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 2d 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Design Command
Plan comprehensive test coverage strategy for new or existing code using the test-architect subagent.
Phase 1: Understand the Target
Analyze what needs testing:
- If
$ARGUMENTSprovided, focus on specified files/features - Read the target code and understand:
- Public interfaces and contracts
- Business logic and edge cases
- Dependencies and integrations
- Error handling paths
Phase 2: Test Pyramid Analysis
Determine appropriate test distribution:
/\
/ \ E2E Tests (Few)
/----\ - Critical user journeys
/ \ - Cross-system validation
/--------\
/ \ Integration Tests (Some)
/ \ - API contracts
/ \ - Database interactions
/----------------\ - External service mocks
/ \
/ Unit Tests \ (Many)
/ (Foundation) \
/----------------------\
Unit Test Candidates
- Pure functions
- Business logic
- Data transformations
- Validation rules
- Edge cases and boundaries
Integration Test Candidates
- API endpoints
- Database operations
- Message queues
- External service calls
- Authentication flows
E2E Test Candidates
- Critical user journeys
- Checkout/payment flows
- Authentication sequences
- Multi-step workflows
Phase 3: Test Case Generation
For each identified test target, design:
Test Case Template
Feature: [Feature Name]
Scenario: [Scenario Description]
Given: [Initial State]
When: [Action Taken]
Then: [Expected Outcome]
Edge Cases:
- [Edge case 1]
- [Edge case 2]
Error Cases:
- [Error scenario 1]
- [Error scenario 2]
Coverage Strategy
- Happy path (normal flow)
- Boundary conditions
- Error handling
- Null/undefined inputs
- Concurrent access (if applicable)
- Performance constraints
Phase 4: Framework Detection & Setup
Detect existing test infrastructure:
- Jest/Vitest for JavaScript/TypeScript
- pytest for Python
- go test for Go
- JUnit for Java
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.
- 2d ago First seen · 187 lines · 9 tokens per session scan A e2525a63c182
test-design is a command published in the GitHub repository CloudAI-X/opencode-workflow (274 stars, last pushed 7mo ago), licensed MIT. It adds 9 tokens to every session and 987 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 2026-08-30.
Other commands, from other repositories
verify
Adversarial spec-vs-implementation verification for a completed task. Dispatches the spec-mentor subagent with fresh context (no anchoring bias), parses its verdict (PASS / DRIFT / NEEDS-MARTY), and updates the verification queue. The v7.4.0 architectural replacement for a dedicated "mentor session.".
research
Enter RESEARCH mode for information gathering.
criar-skill
Use when creating new skills, automations, or specialized knowledge packages. Keywords: criar skill, nova skill, automatizar, conhecimento, TDD skill.
research
Delegate a thorough research investigation to the agy:runner subagent.
station
You are helping the user work with Station - the self-hosted AI agent orchestration platform.
delegate
Delegate investigation, an explicit fix request, or follow-up work to the Grok delegate subagent.