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/dansasser/claude-code-marketplace/reviewgit clone --depth 1 https://github.com/dansasser/claude-code-marketplaceWrote 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/dansasser/claude-code-marketplace/review)<a href="https://agentmods.dev/commands/dansasser/claude-code-marketplace/review"><img src="https://agentmods.dev/badge/commands/dansasser/claude-code-marketplace/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 5.1 | $0.00000 | $0.00932 |
| Opus 5 | $0.00000 | $0.00466 |
| Sonnet 5 | $0.00000 | $0.00186 |
| Haiku 4.5 | $0.00000 | $0.00093 |
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 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
Code Review with Ollama
Perform comprehensive code review using ollama agents.
Usage: /review <file_or_directory> [strictness]
Strictness Levels:
quick: Fast review, major issues onlystandard: Balanced review (default)thorough: Deep analysis with security, quality, and architecture
Examples:
/review src/auth.py- Standard review of auth module/review src/api/ thorough- Deep review of API directory/review main.py quick- Quick check
You are performing a code review by orchestrating ollama agents.
Target: $1 Strictness: ${2:-standard}
Your Process:
-
Determine Scope:
- Single file: Direct analysis via ollama-task-router
- Directory: Use directory operations for efficient review
- Large codebase: Focus on changed files or critical paths
-
Directory Operations for Reviews:
When reviewing directories, use these operations:
Strictness Directory Operations Purpose quick @./dir/:search:TODOFind obvious issues standard @./dir/:tree+@./dir/:search:FIXMEStructure + known issues thorough @./dir/:tree+ multiple:search:patternsFull analysis Example Directory Review Prompts:
Quick:
@./src/:search:TODO+@./src/:search:FIXMEStandard:@./src/:tree+@./src/:search:TODO+@./src/:search:HACKThorough:@./src/:tree+ security patterns + quality patterns -
Select Review Strategy:
Quick Review: Invoke ollama-task-router agent:
- Request: Quick code review focusing on critical bugs and security
- Target: $1
- For directories: Use
@./dir/:search:for obvious issues - Agent handles model selection and execution
Standard Review: Invoke ollama-task-router agent:
- Request: Standard code review
- Checklist: Security, quality, bugs, performance, best practices
- Target: $1
- For directories: Use
@./dir/:treefor structure +:search:for issues
Thorough Review: Invoke ollama-parallel-orchestrator agent:
- Perspectives: security, quality, architecture, testing
- Target: $1
- For directories: Each perspective uses appropriate directory operations
- Multi-angle comprehensive analysis
-
Review Checklist (for agent to cover):
- Security: Injection, XSS, auth issues, secrets in code
- Quality: Naming, structure, complexity, duplication
- Bugs: Logic errors, edge cases, error handling
- Performance: Inefficient algorithms, memory leaks
- Best Practices: Language idioms, design patterns
- Testing: Test coverage, test quality
-
Your Role:
- Invoke appropriate agent based on strictness level
- Receive agent's analysis
- Format results for user
- Prioritize findings by severity
-
Report Format:
## Code Review Summary **File/Directory:** $1 **Strictness:** ${2:-standard} ### Critical Issues (Fix Immediately) - [From agent analysis] ### Major Issues (Fix Soon) - [From agent analysis] ### Minor Issues (Consider Fixing) - [From agent analysis] ### Positive Observations - [From agent analysis] ### Recommendations - [Actionable items] -
Priority Levels:
- CRITICAL: Security vulnerabilities, data loss risks
- MAJOR: Bugs, performance issues, maintainability problems
- MINOR: Style issues, minor optimizations
Directory Review Benefits:
@./dir/:treeshows full project structure in ~500 tokens@./dir/:search:TODOfinds all incomplete work instantly@./dir/:search:FIXMElocates known issues across codebase- More comprehensive than reviewing files individually
Remember: Agents handle the heavy analysis. You orchestrate and present results clearly.
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 · 119 lines · 0 tokens per session scan A 653e08ff7de4
review is a command published in the GitHub repository dansasser/claude-code-marketplace (9 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 932 tokens. 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
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.
constitution
Create or update the project constitution from interactive or provided principle inputs.
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.