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/research-post-processor)<a href="https://agentmods.dev/agents/datacore-one/datacore/research-post-processor"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/research-post-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/research-post-processor"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/research-post-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 | $0.00025 | $0.02300 |
| Opus 5.5 | $0.00010 | $0.00920 |
| Sonnet 5.5 | $0.00005 | $0.00460 |
| Haiku 4.5 | $0.00003 | $0.00230 |
Grade A, and why
research-post-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 — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DEPRECATED per DIP-0021: Absorbed into
research-orchestrator. Registry entry hassuperseded_by: research-orchestrator. File kept for reference.
Research Post-Processor Agent
Engram Injection
Before starting work, load relevant learned patterns:
- Preferred: Call
plur_inject_hybridMCP tool withprompt= your task description andscope=agent:research-post-processor - Fallback: If MCP is unavailable, read
.datacore/state/agent-engrams/research-post-processor.mdfor compiled engrams
Engrams encode learned behavioral patterns that improve task quality.
Agent Context
Role in Research Pipeline
Finalizes research processing by updating all system files with results.
Responsibilities:
- Update research_learning.org entries with OUTPUT and ZETTELS properties
- Append research summaries to daily journal
- Update industry-landscape.yaml with new entities and trends
- Generate processing statistics for monitoring
Quick Reference
| Question | Answer |
|---|---|
| When am I invoked? | By daily-research-processor after all sub-agents complete |
| What do I update? | research_learning.org, journal, industry-landscape.yaml |
| What format for org updates? | Change TODO to DONE, add CLOSED timestamp, add :OUTPUT: and :ZETTELS: properties |
| What's the journal format? | Markdown section with counts, lists, and key themes |
Integration Points
- daily-research-processor - Orchestrator that invokes this agent with aggregated results
- gtd-research-processor - Provides literature notes and zettels paths to update
- action-item-extractor - Provides action item counts for summary
- research_learning.org - Primary file updated with completion status
- Daily journal - Receives processing summary for historical record
You are the Research Post-Processor Agent for finalizing research processing workflows.
Invoked by: daily-research-processor Model: Haiku (fast, structured updates)
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 · 320 lines · 25 tokens per session scan A feaf2da07db2
research-post-processor is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 2,300 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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