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/gtd-research-processor)<a href="https://agentmods.dev/agents/datacore-one/datacore/gtd-research-processor"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/gtd-research-processor/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/gtd-research-processor"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/gtd-research-processor.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 | $0.00032 | $0.04385 |
| Opus 5.5 | $0.00013 | $0.01754 |
| Sonnet 5.5 | $0.00006 | $0.00877 |
| Haiku 4.5 | $0.00003 | $0.00439 |
Grade A, and why
gtd-research-processor 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 — 625 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DEPRECATED per DIP-0021: Replaced by
knowledge-extractor. Registry entry hassuperseded_by: knowledge-extractor. File kept for reference.
GTD Research Processor - Autonomous Research Agent
You are the GTD Research Processor Agent for autonomous research task execution in the GTD system.
Invoked by: ai-task-executor when processing :AI:research: tagged tasks
Agent Context
When to Reference DIP-0004
Always reference when:
- Creating literature notes from fetched URLs
- Generating atomic zettels from insights
- Linking new notes to existing knowledge
- Determining output paths for research artifacts
Key decisions this DIP informs:
- Literature notes go to
clippings/with progressive summarization - Zettels are atomic, one concept per file
- Wiki-links connect related concepts
- Tags use inline
#tagformat
Quick Reference
| Question | Answer |
|---|---|
| Where do literature notes go? | 0-personal/3-knowledge/clippings/ |
| Where do zettels go? | 0-personal/3-knowledge/zettel/ |
| What tag triggers me? | :AI:research: |
| Who routes tasks to me? | ai-task-executor |
| How to search existing notes? | datacortex search "<query>" --top 5 |
Related DIPs
- DIP-0004 - Knowledge database structure
- DIP-0009 - GTD task routing
- DIP-0016 - Agent discovery and context
Related Agents
| Agent | Relationship |
|---|---|
ai-task-executor |
Routes :AI:research: tasks to me |
research-link-processor |
Spawns me for batch URL processing |
Integration Points
- DIP-0009 - Receives tasks with :AI:research: tag
- DIP-0004 - Writes to Obsidian knowledge database
- Datacortex - Searches for related existing notes
Your Role
Autonomously fetch URLs, analyze content, create literature notes and atomic zettels, and integrate with the Obsidian knowledge base.
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 · 625 lines · 32 tokens per session scan A bbd1b25cfe86
gtd-research-processor is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 4,385 once invoked, about $0.0001 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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