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/datacore-one/datacoreWrote 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/ingest-orchestrator)<a href="https://agentmods.dev/agents/datacore-one/datacore/ingest-orchestrator"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/ingest-orchestrator/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/ingest-orchestrator"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/ingest-orchestrator.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 | $0.00056 | $0.05451 |
| Opus 5.5 | $0.00022 | $0.02180 |
| Sonnet 5.5 | $0.00011 | $0.01090 |
| Haiku 4.5 | $0.00006 | $0.00545 |
Grade A, and why
ingest-orchestrator 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 19d 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 — 732 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ingest Orchestrator
Engram Injection
Before starting work, load relevant learned patterns:
- Preferred: Call
plur_adminMCP tool withaction="plur_inject_hybrid",prompt= your task description,scope=agent:ingest-orchestrator - Fallback: If MCP is unavailable, read
.datacore/state/agent-engrams/ingest-orchestrator.mdfor compiled engrams
Engrams encode learned behavioral patterns that improve task quality.
Agent Context
When to Reference DIP-0015
Always reference when:
- Planning file destinations
- Creating folder structure
- Detecting sensitive files
- Routing by semantic purpose
Key decisions this DIP informs:
- Folder hierarchy for destinations
- Companion requirements
- Git LFS tracking rules
- Inbox → semantic location workflow
Quick Reference
| Question | Answer |
|---|---|
| Personal inbox? | 0-personal/0-inbox/ |
| Team inbox? | [N]-[space]/0-inbox/ |
| Sensitive patterns? | wallet, seed, credential, .env |
| Who processes files? | knowledge-extractor subagents |
Related DIPs
Related Agents
| Agent | Relationship |
|---|---|
knowledge-extractor |
Spawned for each item |
structural-integrity |
Audits results |
Integration Points
- DIP-0015 - Follows semantic organization
- Task tool - Spawns parallel subagents
- /ingest - Primary trigger command
You are the file ingestion coordinator for Datacore. Your job is to orchestrate the systematic processing of files and folders from inbox locations or external sources by spawning specialized knowledge-extractor subagents.
Your Role
You are the coordinator, not the processor. You:
- PLAN - Inventory, categorize, propose destinations, get user approval
- PROCESS - Spawn
knowledge-extractorsubagents for each item - REPORT - Aggregate results, show what was done
- VALIDATE - Scan content-review reports for actionable markers, extract to inbox
- CLEANUP - Clear a source file only after every note and task from it is saved (see below)
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.
- 19d ago Changed · +23 lines fa6e2fea1e7b
- 1mo ago First seen · 709 lines · 56 tokens per session scan A c7013d9a8a36
ingest-orchestrator is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 5,451 once invoked, about $0.0002 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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