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/parallelgit 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 | $0.00010 | $0.00972 |
| Opus 5 | $0.00005 | $0.00486 |
| Sonnet 5 | $0.00002 | $0.00194 |
| Haiku 4.5 | $0.00001 | $0.00097 |
Grade A, and why
parallel 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Execution Command
Demonstrates the parallel execution pattern from claude-workflow-v2 by launching multiple independent subagents in a single message.
Core Principle
ALL Task calls MUST be in a SINGLE assistant message for true parallelism.
If Task calls are in separate messages, they run sequentially, negating the performance benefit.
Phase 1: Analyze the Request
Parse $ARGUMENTS to determine parallel tasks:
- Task-based: Multiple independent tasks to execute
- Directory-based: Multiple directories to analyze
- Perspective-based: Multiple review angles on same code
If no arguments, demonstrate with a default parallel analysis of the project.
Phase 2: Identify Independent Tasks
For parallelization, tasks must be:
- Independent: No dependencies between them
- Non-conflicting: Don't modify the same files
- Self-contained: Each can complete without the other
Examples of good parallel candidates:
- Code review + Security audit + Test analysis
- Analyze src/ + Analyze lib/ + Analyze tests/
- Check TypeScript + Check ESLint + Check tests
Phase 3: Execute in Parallel
Launch ALL subagents in a SINGLE message using the Task tool:
In ONE message, spawn multiple Task calls:
Task 1: "@code-reviewer Review the authentication module for quality issues"
Task 2: "@security-auditor Check authentication for vulnerabilities"
Task 3: "@test-architect Analyze test coverage for authentication"
Parallelization Patterns
Pattern A: Multi-Perspective Review
Spawn in parallel:
- Logic Reviewer: Focus on correctness and edge cases
- Performance Reviewer: Focus on efficiency and bottlenecks
- Security Reviewer: Focus on vulnerabilities
- Maintainability Reviewer: Focus on code quality
Pattern B: Directory Parallelization
Spawn in parallel:
- Subagent 1: Analyze src/api/
- Subagent 2: Analyze src/models/
- Subagent 3: Analyze src/utils/
Pattern C: Full Verification Suite
Spawn in parallel:
- Type Checker: Run TypeScript/mypy
- Linter: Run ESLint/ruff
- Test Runner: Execute test suite
- Security Scanner: Check for vulnerabilities
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 · 162 lines · 10 tokens per session scan A cf3bc3104991
parallel is a command published in the GitHub repository CloudAI-X/opencode-workflow (274 stars, last pushed 7mo ago), licensed MIT. It adds 10 tokens to every session and 972 once invoked, about $0.0001 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
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.