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 knitli/toolshed --skill onboardinggit clone --depth 1 https://github.com/knitli/toolshedWrote 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/knitli/toolshed/onboarding)<a href="https://agentmods.dev/skills/knitli/toolshed/onboarding"><img src="https://agentmods.dev/badge/skills/knitli/toolshed/onboarding/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/knitli/toolshed/onboarding"><img src="https://agentmods.dev/badge/skills/knitli/toolshed/onboarding.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00000 | $0.01493 |
| Opus 5.5 | $0.00000 | $0.00597 |
| Sonnet 5.5 | $0.00000 | $0.00299 |
| Haiku 4.5 | $0.00000 | $0.00149 |
Grade A, and why
onboarding scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl --fail-with-body -sS \ How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: codeweaver-onboarding version: 1.0.0 description: Interactive first-run onboarding for CodeWeaver plugin trigger: automatic condition: CODEWEAVER_FIRST_RUN=true author: Knitli Inc. license: MIT OR Apache-2.0
CodeWeaver First-Run Onboarding
You are guiding a user through their first-time setup of CodeWeaver, a semantic code search MCP server. This onboarding runs once and should be friendly, clear, and efficient.
Your Goal
Walk the user through selecting an embedding provider, configuring credentials, and verifying the setup works. Be conversational but concise.
Setup Flow
1. Welcome & Overview
Greet the user warmly and explain what's about to happen:
Welcome to CodeWeaver! 👋
I'll help you get set up in just a few minutes. We need to:
1. Choose an embedding provider (for semantic search)
2. Configure your API credentials (stored securely)
3. Index your codebase
4. Verify everything works
Let's get started!
2. Embedding Provider Selection
Explain the options and make a recommendation:
Recommended: Voyage AI (Voyage-4)
- Best-in-class code embeddings
- Optimized for semantic code search
- Requires API key (free tier available)
- Get API key at voyage.ai
Alternative: FastEmbed (Local)
- Runs entirely on your machine
- No API key needed
- Good quality, slightly slower
- Zero-cost option
Question: "Which provider would you like to use? (voyage/fastembed)"
Wait for user response. If they choose Voyage, proceed to step 3. If FastEmbed, skip to step 4.
3. API Key Collection (Voyage only)
For Voyage AI:
Great choice! You'll need a Voyage AI API key.
Get one here: https://voyage.ai (free tier available)
Once you have your API key, paste it below. It will be stored securely in your system keychain.
Wait for the user to provide the API key.
Validation: Test the API key works by assigning it inline so it doesn't need to be exported first:
# Use the bash tool to test the key; this will fail on non-2xx responses
VOYAGE_API_KEY="<key-provided-by-user>" \
curl --fail-with-body -sS \
-H "Authorization: Bearer ${VOYAGE_API_KEY}" \
-H "Content-Type: application/json" \
https://api.voyageai.com/v1/models
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.
- 1mo ago First seen · 220 lines · 0 tokens per session scan A 5193eb797d6e
onboarding is a skill published in the GitHub repository knitli/toolshed (1 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,493 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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