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 skills add KarmaloopAI/Jiva --skill code-reviewgit clone --depth 1 https://github.com/KarmaloopAI/JivaWrote 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/skills/karmaloopai/jiva/code-review)<a href="https://agentmods.dev/skills/karmaloopai/jiva/code-review"><img src="https://agentmods.dev/badge/skills/karmaloopai/jiva/code-review.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00061 | $0.00865 |
| Opus 5 | $0.00030 | $0.00432 |
| Sonnet 5 | $0.00012 | $0.00173 |
| Haiku 4.5 | $0.00006 | $0.00086 |
Grade A, and why
code-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 8d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Skill
Overview
Perform comprehensive code reviews analyzing bugs, style issues, performance bottlenecks, security vulnerabilities, and adherence to best practices.
Workflow
1. Scan Code Structure
- Use
viewtool to read all relevant files in the codebase - Identify file types, frameworks, and languages used
- Map dependencies and module relationships
2. Analyze Code Quality
Check for the following categories:
Bugs & Logic Errors:
- Null/undefined handling
- Off-by-one errors
- Race conditions
- Memory leaks
- Incorrect algorithm implementation
Security Issues:
- SQL injection vulnerabilities
- XSS vulnerabilities
- Authentication/authorization flaws
- Sensitive data exposure
- Unsafe dependencies
Performance Problems:
- Inefficient algorithms (O(n²) where O(n) possible)
- Unnecessary database queries
- Memory overuse
- Blocking operations
- Missing caching
Code Style:
- Naming conventions
- Code formatting inconsistencies
- Magic numbers/strings
- Dead code
- Overly complex functions
Best Practices:
- DRY (Don't Repeat Yourself) violations
- SOLID principles adherence
- Error handling patterns
- Testing coverage
- Documentation quality
3. Categorize Findings
Group issues by:
- Critical: Security vulnerabilities, data loss risks
- High: Bugs that cause crashes/errors
- Medium: Performance issues, maintainability problems
- Low: Style issues, minor improvements
4. Provide Solutions
For each issue:
- Explain WHY it's a problem
- Show the problematic code snippet
- Provide a SPECIFIC fix with code examples
- Explain the benefits of the fix
5. Generate Report
Structure the output as:
# Code Review Report
## Summary
- Total files reviewed: X
- Issues found: Y (Z critical, W high, V medium, U low)
## Critical Issues
[List critical issues with fixes]
## High Priority Issues
[List high priority issues with fixes]
## Medium Priority Issues
[List medium priority issues with fixes]
## Low Priority Issues
[List low priority issues with fixes]
## Strengths
[Mention good practices found in the code]
## Recommendations
[Overall suggestions for improvement]
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 139 lines · 61 tokens per session scan A 8ac1cfcb1e48
code-review is a skill published in the GitHub repository KarmaloopAI/Jiva (35 stars, last pushed 23d ago), licensed MIT. It adds 61 tokens to every session and 865 once invoked, about $0.0003 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 skills, from other repositories
hqe
Comprehensive codebase health auditing, remediation, and verification skill based on the canonical HQE Protocol v5.0.0.
cn-check
Install and run the Continue CLI (cn) to execute AI agent checks on local code changes. Use when asked to "run checks", "lint with AI", "review my changes with cn", or set up Continue CI locally.
contribute-to-eliza
Finish and prove a scoped elizaOS GitHub issue, or independently review and repair an open elizaOS pull request. Use when contributing compute to elizaOS by selecting unclaimed work, implementing or reviewing changes, adding real tests and evidence, validating artifacts, or preparing a contribution for maintainer…
printing-press-output-review
Internal sub-skill: agentic review of a printed CLI's sampled command output for plausibility issues that rule-based checks can't encode (substring-match relevance, format bugs, silent source drops, ranking failures). Invoked via the Skill tool by the main printing-press skill at Phase 4.85 and printing-press-polish…
claw-admin
Claw system administration: service management, IM connections, logs, cron, and workspace diagnostics. Use when the user asks to manage claw services, connect/disconnect IM platforms, view logs, or perform system-wide operations.
pr-writing-review
Extract and analyze writing improvements from GitHub PR review comments. Use when asked to show review feedback, style changes, or editorial improvements from a GitHub pull request URL. Handles both explicit suggestions and plain text feedback. Produces structured output comparing original phrasing with reviewer…