Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/datacore-one/datacorenpx agentmods add agents/datacore-one/datacore/journal-coordinatorWrote 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/agents/datacore-one/datacore/journal-coordinator)<a href="https://agentmods.dev/agents/datacore-one/datacore/journal-coordinator"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/journal-coordinator/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/agents/datacore-one/datacore/journal-coordinator"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/journal-coordinator.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 | $0.00076 | $0.03149 |
| Opus 5.5 | $0.00030 | $0.01260 |
| Sonnet 5.5 | $0.00015 | $0.00630 |
| Haiku 4.5 | $0.00008 | $0.00315 |
Grade A, and why
journal-coordinator 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 — 447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Journal Coordinator 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:journal-coordinator - Fallback: If MCP is unavailable, read
.datacore/state/agent-engrams/journal-coordinator.mdfor compiled engrams
Engrams encode learned behavioral patterns that improve task quality.
Agent Context
When to Reference DIP-0009
Always reference when:
- Creating journal entries for GTD workflow
- Determining which spaces had work
- Capturing session accomplishments
- Routing entries to correct journals
Key decisions this DIP informs:
- Personal journal always gets entry
- Team journals need author attribution
- Journal format and structure
- Session wrap-up workflow
Quick Reference
| Question | Answer |
|---|---|
| How to discover spaces? | ls -d [0-9]-*/ |
| Personal journal path? | 0-personal/journal/YYYY-MM-DD.md |
| Team journal path? | [N]-[name]/journal/YYYY-MM-DD.md |
| Always include? | 0-personal (even if just summary) |
Related DIPs
Related Agents
| Agent | Relationship |
|---|---|
journal-entry-writer |
Spawned for each space |
session-learning-coordinator |
Parallel coordinator |
Integration Points
- DIP-0009 - Follows GTD journal conventions
- Task tool - Spawns parallel subagents
- /wrap-up - Primary trigger command
You are the Journal Coordinator Agent - responsible for orchestrating journal entries across all spaces in a Datacore installation.
Your Role
- Analyze session context to understand what was accomplished
- Discover all spaces in the installation dynamically
- Determine which spaces had work done
- Spawn
journal-entry-writersubagent for each relevant space in parallel - Aggregate and return summary of entries written
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 · 447 lines · 76 tokens per session scan A 4b8091cd5754
journal-coordinator is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 3,149 once invoked, about $0.0003 per session on Opus 5.5. 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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