waza

waza is a skill for Claude Code, Codex from microsoft/waza. It costs 145 tokens per session (1,804 once invoked), scanned A, original, MIT.

A command-line tool for evaluating AI-agent skills with structured benchmark cases written in YAML. YAML is a readable text format for configuration and test data.

In plain words
What is it for?
Use it to create evaluation suites, run benchmarks, generate tests from a skill file, compare result files, and improve a skill's compliance.
Why use it?
It provides repeatable tests and scoring so you can measure whether a skill follows its instructions and compare different results.

Skill for Claude CodeCodex

About the project

microsoft/waza is a Go command-line tool for building and evaluating AI agent skills through test suites, benchmarks, and model comparisons. It is for developers who need to measure and improve how reliably agent skills work. The catalogue entries are Waza's own skills, instructions, agent, and MCP integration.

microsoft/waza · 1,294 stars · on GitHub

Install

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.

agentmods
npx agentmods add skills/microsoft/waza/waza
Any agent
npx skills add microsoft/waza --skill waza
Clone the repo
git clone --depth 1 https://github.com/microsoft/waza

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for waza

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/waza/waza.svg)](https://agentmods.dev/skills/microsoft/waza/waza)
Your own site
<a href="https://agentmods.dev/skills/microsoft/waza/waza"><img src="https://agentmods.dev/badge/skills/microsoft/waza/waza.svg" alt="Measured on agentmods" height="20"></a>
Per session 145 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,804 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00145 $0.01804
Opus 5 $0.00072 $0.00902
Sonnet 5 $0.00029 $0.00361
Haiku 4.5 $0.00015 $0.00180

Measured 5d ago against content hash e7ef60562bbf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

waza 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.

skills/waza/SKILL.md · 215 lines

How it starts

The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Waza

"The way of technique — measure, refine, master."

A Go CLI tool for evaluating AI agent skills through structured benchmarks. Define test cases in YAML, run them against agent engines, and validate results with pluggable scoring validators.

Help

When user says "waza help" or asks how to use waza:

╔══════════════════════════════════════════════════════════════════╗
║  WAZA - CLI Tool for Evaluating Agent Skills                     ║
╠══════════════════════════════════════════════════════════════════╣
║                                                                  ║
║  COMMANDS:                                                       ║
║    waza run <eval.yaml>        # Run an evaluation benchmark     ║
║    waza init [directory]       # Initialize a new eval suite     ║
║    waza generate <SKILL.md>    # Generate eval from SKILL.md     ║
║    waza compare <r1> <r2> ...  # Compare result files            ║
║    waza dev [skill-path]       # Improve SKILL.md compliance     ║
║                                                                  ║
║  RUN FLAGS:                                                      ║
║    --context-dir, -c   Fixtures directory (default: ./fixtures)  ║
║    --output, -o        Save results JSON to file                 ║
║    --verbose, -v       Verbose output                            ║
║    --task, -t          Filter tasks by name (repeatable)         ║
║    --parallel, -p      Run tasks in parallel                     ║
║    --workers, -w       Number of parallel workers                ║
║    --transcript-dir    Save per-task transcripts                 ║
║                                                                  ║
║  COMPARE FLAGS:                                                  ║
║    --format, -f        Output format: table or json              ║
║                                                                  ║
║  GENERATE FLAGS:                                                 ║
║    --output-dir, -d    Output directory for generated files      ║
║                                                                  ║
║  DEV FLAGS:                                                      ║
║    --target            Adherence level: low|medium|high          ║
║    --max-iterations    Max improvement iterations (default: 5)   ║
║    --auto              Auto-apply without prompting              ║
║                                                                  ║
║  WORKFLOW:                                                       ║
║    1. waza init my-eval        # Scaffold eval suite             ║
║    2. Edit eval.yaml + tasks   # Define test cases               ║
║    3. waza run eval.yaml -v    # Execute benchmark               ║
║    4. waza compare a.json b.json  # Cross-model comparison       ║
║                                                                  ║
║  FIXTURE ISOLATION:                                              ║
║    Each task gets a fresh temp workspace with fixtures copied    ║
║    in. Original fixtures are never modified.                     ║
║                                                                  ║
╚══════════════════════════════════════════════════════════════════╝

Read the full file on GitHub · 215 lines

Changes

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.

  1. 5d ago First seen · 215 lines · 145 tokens per session scan A e7ef60562bbf

Subscribe to this mod's changes

waza is a skill published in the GitHub repository microsoft/waza (1,294 stars, last pushed 3d ago), licensed MIT. It adds 145 tokens to every session and 1,804 once invoked, about $0.0007 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.

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