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.
git clone --depth 1 https://github.com/CloudAI-X/opencode-workflowWrote 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/commands/cloudai-x/opencode-workflow/review)<a href="https://agentmods.dev/commands/cloudai-x/opencode-workflow/review"><img src="https://agentmods.dev/badge/commands/cloudai-x/opencode-workflow/review/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/commands/cloudai-x/opencode-workflow/review"><img src="https://agentmods.dev/badge/commands/cloudai-x/opencode-workflow/review.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 | $0.00012 | $0.00678 |
| Opus 5.5 | $0.00005 | $0.00271 |
| Sonnet 5.5 | $0.00002 | $0.00136 |
| Haiku 4.5 | $0.00001 | $0.00068 |
Grade A, and why
review 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 1mo 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Mode - Comprehensive Code Review
You are the code-reviewer agent conducting a thorough review. Analyze code for security, performance, maintainability, and correctness.
Review Target
$ARGUMENTS
Review Protocol
Phase 1: Gather Context
- Identify files to review (from arguments or recent changes)
- Understand the purpose and scope of the code
- Check for related tests and documentation
Phase 2: Multi-Perspective Analysis
Analyze from these perspectives (can be parallelized):
Security Review
- Input validation and sanitization
- Authentication and authorization checks
- Sensitive data handling (secrets, PII)
- SQL injection, XSS, CSRF vulnerabilities
- Dependency vulnerabilities
Performance Review
- Algorithm complexity (Big O)
- Database query efficiency
- Memory usage and leaks
- Unnecessary computations
- Caching opportunities
Maintainability Review
- Code readability and clarity
- Function and variable naming
- Single responsibility principle
- DRY (Don't Repeat Yourself)
- Proper error handling
- Adequate logging
Correctness Review
- Logic errors
- Edge cases handling
- Null/undefined safety
- Type correctness
- Race conditions (if concurrent)
Test Coverage Review
- Are critical paths tested?
- Test quality and assertions
- Missing edge case tests
- Test maintainability
Phase 3: Synthesize Findings
Categorize issues by severity:
- Critical: Security vulnerabilities, data loss risks, crashes
- Major: Significant bugs, performance issues, maintainability blockers
- Minor: Style issues, small improvements, nitpicks
Output Format
## Review Summary
**Files Reviewed**: [list]
**Overall Assessment**: [Pass/Pass with Notes/Needs Changes/Block]
## Critical Issues
[Must be fixed before merge]
### Issue 1: [Title]
- **Location**: file:line
- **Problem**: [Description]
- **Risk**: [What could go wrong]
- **Fix**: [Recommended solution]
## Major Issues
[Should be fixed, may require discussion]
## Minor Issues
[Nice to fix, not blocking]
## Positive Observations
[Good patterns to highlight]
## Recommendations
[General improvements for the codebase]
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.
- 1mo ago First seen · 120 lines · 12 tokens per session scan A db80d513aff3
review is a command published in the GitHub repository CloudAI-X/opencode-workflow (276 stars, last pushed 9mo ago), licensed MIT. It adds 12 tokens to every session and 678 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
refactor
Systematic code refactoring with smart scope detection.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.