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 skills/tw93/waza/thinknpx skills add tw93/Waza --skill thinkgit 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/skills/tw93/waza/think)<a href="https://agentmods.dev/skills/tw93/waza/think"><img src="https://agentmods.dev/badge/skills/tw93/waza/think.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 | $0.00056 | $0.03209 |
| Opus 5 | $0.00028 | $0.01605 |
| Sonnet 5 | $0.00011 | $0.00642 |
| Haiku 4.5 | $0.00006 | $0.00321 |
Grade A, and why
think 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 today.
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
1 near-identical copy found in the catalogue:
- think — 92% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Think: Design and Validate Before You Build
Prefix your first line with 🥷 inline, not as its own paragraph.
Turn a rough idea into an approved plan. No code, no scaffolding, no pseudo-code until the user approves.
Give opinions directly. Take a position and state what evidence would change it. Avoid "That's interesting," "There are many ways to think about this," "You might want to consider."
Outcome Contract
- Outcome: a rough idea becomes a decision-complete recommendation or implementation plan.
- Done when: the goal, success criteria, constraints, chosen approach, rejected tradeoffs, tests, and handoff steps are concrete enough to execute without re-deciding.
- Evidence: current repo state, project docs, live external docs when relevant, prior decisions, constraints, and explicit user preferences.
- Output: one recommended direction or a handoff plan with assumptions and verification steps.
Durable Context Preflight
See references/durable-context.md for when durable context is in scope and the redaction gate that applies before any of it becomes a durable rule.
For /think: current repo state and live docs override memory. Lock durable decisions and preferences before asking questions, and do not ask the user to restate an intent that the durable context already establishes unless it is risky, stale, or contradicted by current state.
Before outputting any plan, scan the project's AGENTS.md, CLAUDE.md, .claude/rules/*.md, and any local agent-memory summary if the user pointed at one. If the proposed plan contradicts a "hard rule", "never X", "must Y", or "prefer Z" stated in those files, surface the contradiction in the plan output (one sentence: which rule, which step contradicts it, recommended resolution). Do not silently override the rule. If the rule blocks the plan, stop and ask before continuing.
Lightweight Mode
Activate when the user wants to fix something rather than build something, the problem is already defined, and the only open question is "how to fix it."
What ships with it
1 file 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.
- today Changed · -3 lines 077e05c4edcd
- 4d ago First seen · 184 lines · 56 tokens per session scan A baf37a7f2637
think is a skill published in the GitHub repository tw93/Waza (6,947 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 3,209 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
agent-bridge
Delegate real coding work to a peer AI agent (such as Claude Code, Codex (ChatGPT), or Gemini (Antigravity)) that runs its own full harness, or use that peer as an independent reviewer, adversarial red-team, ideation & planning partner. Trigger when the user says "use agent bridge", "ask ", "delegate to ", "have…
spark-ui
Install and compose Spark UI signature React components such as Widget Stack, Dynamic Island, Interactive Pets, Tactile Highlight, Shimmer Text, Image Trail, Animated Gradient, Ghost Ether, Logo Carousel, QR Code, Receipt, Number Ticker, Spotify Card, Masonry, Keyboard, and Hello from the Spark UI shadcn-compatible…
verify
Build, run, and drive the Spark UI docs site to verify changes end-to-end.
bridge-review
A peer agent reviews the changes via agent-bridge, then verified findings get reported to you and the easy ones fixed right away. Name the peer after the command, e.g. /bridge-review gemini.
rust-engineer
Use when building Rust systems where memory safety, ownership patterns, zero-cost abstractions, and performance optimization are critical for systems programming, embedded development, async applic...
senior-data-engineer
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Kinesis, and modern data stack. Includes data modeling, pipeline orchestration, data quality, streaming quality…