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/grainulation/grainulator/setupnpx skills add grainulation/grainulator --skill setupgit clone --depth 1 https://github.com/grainulation/grainulatorWhat 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 | $0.00061 | $0.01416 |
| Opus 5 | $0.00030 | $0.00708 |
| Sonnet 5 | $0.00012 | $0.00283 |
| Haiku 4.5 | $0.00006 | $0.00142 |
Grade A, and why
setup 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 yesterday.
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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/setup -- Configure and verify Grainulator
The user wants to set up Grainulator or verify that all MCP servers and dependencies are working correctly.
Arguments
$ARGUMENTS
Instructions
Phase 1: Verify core MCP servers
Grainulator bundles three core MCP servers that run locally via npx. Check each one in order:
-
Wheat (research claims engine)
- Purpose: Manages typed claims (
claims.json), compiles sprint state, resolves conflicts, and searches across claims. This is the backbone of every research sprint. - Verify: Call
wheat_status. If it returns sprint data or a "no sprint found" message, the server is healthy. - If it fails: The
@grainulation/wheatnpm package may not be accessible. Ask the user to runnpx -y @grainulation/wheatmanually to check for npm/network issues. - Sprint data (
claims.json,compilation.json) lives in the project root.
- Purpose: Manages typed claims (
-
Mill (format conversion engine)
- Purpose: Converts between document formats (Markdown, HTML, PDF). Used by
/briefand/presentto produce output artifacts. - Verify: Call
mill_formats. If it returns a list of supported formats, the server is healthy. - If it fails: The
@grainulation/millnpm package may not be accessible. Same troubleshooting as Wheat.
- Purpose: Converts between document formats (Markdown, HTML, PDF). Used by
-
Silo (knowledge storage)
- Purpose: Stores and retrieves knowledge packs, manages a graph of connected concepts, and integrates with Confluence. Used by
/researchand/pullfor knowledge reuse across sprints. - Verify: Call
silo_list. If it returns a list (even empty), the server is healthy. - If it fails: The
@grainulation/silonpm package may not be accessible. Note that Silo uses${CLAUDE_PLUGIN_DATA}/silofor persistent storage.
- Purpose: Stores and retrieves knowledge packs, manages a graph of connected concepts, and integrates with Confluence. Used by
Report the status of each server:
MCP Server Status:
wheat ✓ running (claims engine)
mill ✓ running (format conversion)
silo ✓ running (knowledge storage)
If any server fails, show the error and suggest a fix. Do NOT proceed to Phase 2 until all three core servers are confirmed running.
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.
- yesterday First seen · 132 lines · 61 tokens per session scan A 3da530375ad8
setup is a skill published in the GitHub repository grainulation/grainulator (87 stars, last pushed 4mo ago), licensed MIT. It adds 61 tokens to every session and 1,416 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
project-sizing-guide
Software project effort estimation assistant. Outputs three-point estimates (optimistic/most-likely/pessimistic values with confidence intervals), T-shirt sizes, or Function Point Analysis (FPA) counts. Triggered when users ask 'how long will this feature take,' need to assess project workload, perform PERT…
sprint-wrap-up
End-of-sprint checklist — finalize results, clean up worktrees, update docs, prepare for retro. Any agent can run this.
session-wrapup
End-of-session checkpoint — append diary, update active sprint doc with interim results/retro, write tech-lead handoff, commit and push. Use before /compact or at end-of-day. Distinct from sprint-wrap-up which closes a sprint.
shutdown-dev
Cleanly shut down a dev teammate — instruct them to write a context summary to plan/agent-context/{name}.md first, receive their approval, verify process exit. Use for scale-down, rotation, sprint wrap-up.
sprint-planning
Collaborative sprint planning — validate issues, prioritize, get architect/SM input, create task queue. Any agent can facilitate.
sprint-retrospective
Run a sprint retrospective — gather data, analyze incidents, propose action items. Any agent can facilitate.