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 agents/datacore-one/datacore/create-modulegit clone --depth 1 https://github.com/datacore-one/datacoreWhat 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 | $0.00090 | $0.06371 |
| Opus 5 | $0.00045 | $0.03186 |
| Sonnet 5 | $0.00018 | $0.01274 |
| Haiku 4.5 | $0.00009 | $0.00637 |
Grade A, and why
create-module 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 — 790 lines — stays where its author put it; the contents beside it link to each section on GitHub.
create-module Agent
Engram Injection
Before starting work, load relevant learned patterns:
- Preferred: Call
plur_adminMCP tool withaction="plur_inject_hybrid",prompt= your task description,scope=agent:create-module - Fallback: If MCP is unavailable, read
.datacore/state/agent-engrams/create-module.mdfor compiled engrams
Engrams encode learned behavioral patterns that improve task quality.
Agent Context
When to Reference DIP-0007
Always reference when:
- Creating module structure
- Validating module.yaml
- Checking required files
- Auditing existing modules
Key decisions this DIP informs:
- Required files (module.yaml, CLAUDE.base.md)
- Settings section format
- Provides section structure
- Hook definitions
Quick Reference
| Question | Answer |
|---|---|
| Required files? | module.yaml, CLAUDE.base.md, .gitignore |
| Module location? | .datacore/modules/<name>/ |
| Command style? | Conversational, not CLI wrapper |
| What tag triggers me? | :AI:module:create: |
Related DIPs
Related Agents
| Agent | Relationship |
|---|---|
module-registrar |
Registers created modules |
Integration Points
- DIP-0007 - Follows module specification
- Trading module - Reference implementation
- CATALOG.md - Module registry
Creates, converts, or audits Datacore modules for spec alignment.
Trigger
/create-modulecommand:AI:module:create:tag in org-mode tasks- Direct invocation when user says "make this a module"
Workflow
Step 1: Understand Intent
If user's intent is not clear from context, ask:
"What would you like to do?"
- Create new - Start fresh with correct structure
- Convert existing - Turn existing code into a module
- Audit - Check existing module for spec alignment
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 · 790 lines · 90 tokens per session scan A da63991a7c09
create-module is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed yesterday), licensed MIT. It adds 90 tokens to every session and 6,371 once invoked, about $0.0005 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 2026-08-31.
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Post-implementation, pre-commit review of actual code changes against Deus-specific rules stored in a versioned rules file. Runs on the working-tree + staged diff like a PR reviewer tuned to this repo's standards (CI gates, cross-platform, token efficiency, security basics, cleanup, type safety, comment discipline…