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.
git clone --depth 1 https://github.com/grainulation/wheatWrote 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/commands/grainulation/wheat/init)<a href="https://agentmods.dev/commands/grainulation/wheat/init"><img src="https://agentmods.dev/badge/commands/grainulation/wheat/init/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/commands/grainulation/wheat/init"><img src="https://agentmods.dev/badge/commands/grainulation/wheat/init.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 | $0.00634 |
| Opus 5.5 | $0.00000 | $0.00254 |
| Sonnet 5.5 | $0.00000 | $0.00127 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
init 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/init — Bootstrap a Wheat research sprint
You are initializing a new Wheat research sprint. Have a focused conversation with the user to establish:
- What are we figuring out? Get a clear, specific question. Not "should we use X" but "should we use X given constraints Y and Z for audience A."
- Who is the audience? Who needs to be convinced or informed? (engineering leads, CTO, product, finance, etc.)
- What constraints exist? Budget, timeline, tech stack, compliance, team size, existing infrastructure.
- What does done look like? What artifact ends this sprint? A recommendation? A prototype? A go/no-go decision?
Once you have answers:
Step 1: Update CLAUDE.md
Update the Sprint section of CLAUDE.md with the question, audience, constraints, and success criteria.
Step 2: Seed claims.json
Update claims.json with:
meta.question— the sprint questionmeta.initiated— today's date (ISO format)meta.audience— array of audience labelsmeta.phase— set to "define"meta.connectors— empty array
Add constraint claims (type: "constraint") for each hard requirement identified. Use IDs starting with d001. Each claim needs:
{
"id": "d001",
"type": "constraint",
"topic": "<relevant topic>",
"content": "<the constraint>",
"source": { "origin": "stakeholder", "artifact": null, "connector": null },
"evidence": "stated",
"status": "active",
"phase_added": "define",
"timestamp": "<ISO timestamp>",
"conflicts_with": [],
"resolved_by": null,
"tags": []
}
Step 3: Run the compiler
npx @grainulation/wheat compile --summary
Verify compilation succeeds.
Step 4: Generate problem statement
Generate output/problem-statement.html — a clean, self-contained HTML page summarizing the sprint question, audience, constraints, and success criteria. Use the dark theme from the explainer template in templates/. Keep it to a single page — this is the "here's what we're investigating" artifact that can be shared immediately.
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 · 72 lines · 0 tokens per session scan A 2cea6600815b
init is a command published in the GitHub repository grainulation/wheat (20 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 634 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 commands, from other repositories
mcptoon-setup
Set up or repair the mcptoon CLI for this machine (install, verify, diagnose).
safe-build
Build the application for development or production.
local
Command "local" from getsentry/toolkit, covering examples, start the server and tail events (default), run your app with the local server auto-enabled, use a custom port and only show errors and logs (filter out transactions).
debug-files
Command "debug-files" from getsentry/toolkit, covering examples, inspect a debug information file (auto-detects the format), bundle jvm sources with a debug id, exclude additional directories and output as json.
auth
Command "auth" from getsentry/toolkit, covering examples, oauth login (recommended), token login, read-only oauth login and custom oauth scopes.
feedback
Modern User Feedback is stored as Feedback issues. The command always limits issue searches to issue.category:feedback; it does not use the legacy User Reports API.