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/qwickapps/ai-sdlc-workflows/reviewgit clone --depth 1 https://github.com/qwickapps/ai-sdlc-workflowsWrote 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/qwickapps/ai-sdlc-workflows/review)<a href="https://agentmods.dev/commands/qwickapps/ai-sdlc-workflows/review"><img src="https://agentmods.dev/badge/commands/qwickapps/ai-sdlc-workflows/review.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 | $0.00006 | $0.00630 |
| Opus 5 | $0.00003 | $0.00315 |
| Sonnet 5 | $0.00001 | $0.00126 |
| Haiku 4.5 | $0.00001 | $0.00063 |
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 3d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Workflow
You are now in Review Mode. Use this to review code before committing.
Input: $ARGUMENTS (files to review, PR number, branch name, or "staged" for staged changes)
CRITICAL RULES
- Be thorough but practical - focus on meaningful issues
- Prioritize by severity - critical > important > minor
- Include positive feedback - acknowledge good patterns
Interactive Setup
Check if $ARGUMENTS is provided.
If $ARGUMENTS is empty, ask:
"What would you like me to review? Please specify:
- Specific files or directories
- A PR number or branch name
- 'staged' for currently staged changes
- 'recent' for recent commits"
Wait for response before proceeding.
Review Process
Step 1: Understand Context
-
What is being reviewed?
- New feature, bug fix, refactoring?
- What are the requirements/acceptance criteria?
- What files are affected?
-
Gather context:
- Read relevant design docs in
.claude/engineering/ - Understand the expected behavior
- Read relevant design docs in
Step 2: Review Code
Evaluate against these criteria:
Critical (must fix):
- Security vulnerabilities
- Data corruption risks
- Breaking changes without acknowledgment
Important (should fix):
- Performance issues
- Error handling gaps
- Missing tests for critical paths
- Logic errors
Minor (consider fixing):
- Code style inconsistencies
- Minor optimizations
- Documentation gaps
Positive (acknowledge):
- Good patterns used
- Clean implementations
- Effective testing
Step 3: Create Review Report
- Save to:
.claude/engineering/reviews/REVIEW-<id>-<context>.md - Use template from
.claude/templates/REVIEW.md
Step 4: Present Findings
Format:
## Review Summary
**Overall**: APPROVED / APPROVED WITH CHANGES / NEEDS WORK
### Critical Issues (must fix)
- [issue description and recommendation]
### Important Issues (should fix)
- [issue description and recommendation]
### Minor Issues (consider)
- [issue description]
### Positive Notes
- [good patterns observed]
### Verification Checklist
- [ ] Tests pass
- [ ] No security issues
- [ ] Error handling adequate
- [ ] Documentation updated
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.
- 3d ago First seen · 123 lines · 6 tokens per session scan A 834435c4214f
review is a command published in the GitHub repository qwickapps/ai-sdlc-workflows (2 stars, last pushed 5mo ago), licensed MIT. It adds 6 tokens to every session and 630 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 commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.