Waku Agent is a local-first personal AI assistant whose readable code implements the agent loop, memory, and evaluation system. It is for people who want an assistant they can run and understand on their own laptop, with memory stored in SQLite and built-in testing. The catalogue add-ons support its agent workflow.
Borrowing it
Nothing to install: this file belongs to ShenSeanChen/waku-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ShenSeanChen/waku-agent/main/.claude/skills/new-tool/SKILL.mdgit clone --depth 1 https://github.com/ShenSeanChen/waku-agentWrote 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/shenseanchen/waku-agent/new-tool)<a href="https://agentmods.dev/skills/shenseanchen/waku-agent/new-tool"><img src="https://agentmods.dev/badge/skills/shenseanchen/waku-agent/new-tool/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shenseanchen/waku-agent/new-tool"><img src="https://agentmods.dev/badge/skills/shenseanchen/waku-agent/new-tool.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00042 | $0.00328 |
| Opus 5 | $0.00021 | $0.00164 |
| Sonnet 5 | $0.00008 | $0.00066 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
new-tool 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 12d 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
Procedure
- One file per tool in
waku/tools/, exposingmake_tool(...) -> Tool. Copy the shape ofwaku/tools/calendar.py(the reference implementation). - The tool function must be:
- Idempotent where repeat calls could occur (check-before-insert, like create_event's title+start guard).
- Honest in its return string: say exactly where the artifact went (file path, table) and how the user can see it. Never imply effects the tool doesn't have.
- Local-first by default: write to
.waku/or state.db; real external services go behind env-gated adapters.
- Register it in
waku/tools/__init__.py:build_registry. - Add deterministic eval coverage in
evals/deterministic/:- offline: scripted client fires the tool → assert the artifact (DB row/file)
- a dataset case in
evals/dataset.jsonlfor the live tier
- If the tool needs usage guidance, add a rule to DEFAULT_SOUL
(
waku/runtime/session.py) or a skill inskills/. - Check scope first: the repo ships flagship-task tools only. New capabilities beyond scheduling/notes/messages should be discussed before building.
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.
- 12d ago First seen · 26 lines · 42 tokens per session scan A 5a8d2c719f45
new-tool is a skill published in the GitHub repository ShenSeanChen/waku-agent (1,728 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 328 once invoked, about $0.0002 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
slacrawl
Archive and search Slack workspace messages, threads, and channels via the slacrawl CLI. Supports API sync, Slack export ZIP import, local desktop cache import, and full-text search.
obsidian
Read, search, and create notes in the Obsidian vault.
clip-hand-skill
Expert knowledge for AI video clipping — yt-dlp downloading, whisper transcription, SRT generation, and ffmpeg processing.
twitter-hand-skill
Expert knowledge for AI Twitter/X management — API v2 reference, content strategy, engagement playbook, safety, and performance tracking.
slack-tools
Slack workspace management and automation specialist.
routing-card-authoring
Use whenever a build emits or repairs .agentlas/routing-card.json — the shared card contract for the single-agent builder, the team builder, and the packager. States what belongs in every field, which fields the hub can actually match on, and which fields silently break matching when a sentence leaks into them.