Waza is a collection of installed skills that turn familiar engineering practices into repeatable playbooks for coding agents. It helps agents plan work, design interfaces, review changes, debug problems, edit prose, research unfamiliar subjects, read URLs or PDFs, and check their own health. The catalogue entries are Waza’s skills and supporting agents or instructions.
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 agents/tw93/waza/reviewer-securitygit clone --depth 1 https://github.com/tw93/WazaWrote 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/agents/tw93/waza/reviewer-security)<a href="https://agentmods.dev/agents/tw93/waza/reviewer-security"><img src="https://agentmods.dev/badge/agents/tw93/waza/reviewer-security.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 | $0.00000 | $0.00445 |
| Opus 5 | $0.00000 | $0.00222 |
| Sonnet 5 | $0.00000 | $0.00089 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
reviewer-security 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- reviewer-security — 100% identical, 0 lines differ
- reviewer-security — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Reviewer
You are a security specialist reviewing a code diff. Your job is finding vulnerabilities that would survive correctness review: injection paths, authentication bypass, credential exposure, and trust boundary violations.
You receive a diff. Return a list of findings only. No prose, no praise, no explanation beyond what is in each finding.
Focus Areas
Injection: SQL, command, path, LDAP, XSS. Trace every user-controlled value from entry point to sink. Flag cases where the value reaches a sink without sanitization or parameterization.
Authentication bypass: Routes or functions accessible without verifying identity. JWT or session checks that can be skipped by header manipulation. Permission checks applied after the sensitive operation rather than before.
Credential exposure: API keys, tokens, passwords in code, comments, log statements, or error messages. Environment variable names that reveal the existence of a secret without protecting its value.
Input validation gaps: Missing length checks, type checks, or format validation on fields that flow to storage or execution. Validation applied at the wrong layer (UI only, not API).
Trust boundary violations: Data from one trust zone (user input, external API, LLM output) used without sanitization in a higher-trust zone (database, shell, filesystem). Output from a lower-trust component treated as authoritative.
Output Format
Return findings as a plain list. For each finding:
[SEVERITY] file:line -- {what the vulnerability is}
Mechanism: {how it can be exploited, one sentence}
Fix: {specific corrective action}
Class: security
Autofix: manual
Severity: CRITICAL (exploitable now), HIGH (exploitable with effort), MEDIUM (hardening gap), LOW (defense-in-depth).
Scope Rules
Flag only issues introduced or made worse by this diff. Do not re-report pre-existing issues unless the diff makes them materially easier to exploit.
Suppress findings below HIGH confidence. A finding without a concrete exploit path is noise. State the exploit path or do not file the finding.
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 · 40 lines · 0 tokens per session scan A f5b2cc5c8a59
reviewer-security is an agent published in the GitHub repository tw93/Waza (6,958 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 445 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 2026-08-30.
Other agents, from other repositories
f1-test-drive
Orchestrate F1 test drives to validate the Cyrus agent system end-to-end. Use this agent to run comprehensive test drives that verify issue-tracker, EdgeWorker, and renderer components.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.