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Initialize a new research sprint with a question, audience, and constraints.
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Based on SOC occupation classification
Fast pre-flight health check for all Grainulator MCP servers. Pings each server once, reports status in a table, and provides exact fix commands for any that are down. Use before starting any Grainulator session to avoid wasting time on MCP disconnections.
Generate a compiled decision brief from the current sprint's claims.
Generate a presentation deck from the compiled sprint data.
Size-efficient URL fetch with semantic extraction. Use for ad-hoc web research when you want content without the raw HTML overhead.
Corroborate a claim against an external source URL.
Intent router that detects user intent from plain messages and dispatches to the appropriate skill.
| name | init |
| description | Initialize a new research sprint with a question, audience, and constraints. |
| tools | ["mcp__wheat__wheat_status","Bash","Read"] |
The user wants to start a new research sprint.
$ARGUMENTS
Parse the user's input to extract:
Delegate to the canonical CLI init. Do NOT manually create claims.json or call wheat_add-claim. Run the full init via the Bash tool:
npx -y @grainulation/wheat init --headless \
--question "<question>" \
--audience "<audience>" \
--constraints "<constraint1>; <constraint2>" \
--done "<done criteria>"
This creates all sprint files: claims.json, CLAUDE.md, AGENTS.md, .mcp.json, .gitignore, .claude/commands/wheat/, output directories, and the pre-commit hook. Using the CLI ensures the skill path and CLI path produce identical results.
After init completes, call wheat_status to verify the sprint was created successfully.
Print a summary:
Sprint initialized: <slug>
Question: <question>
Audience: <audience>
Claims: <count>
Next steps:
/research <topic> -- start gathering evidence
/status -- view sprint dashboard