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/research-synthesizergit 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-synthesizer)<a href="https://agentmods.dev/agents/datacore-one/datacore/research-synthesizer"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/research-synthesizer.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.02261 |
| Opus 5 | $0.00020 | $0.01130 |
| Sonnet 5 | $0.00008 | $0.00452 |
| Haiku 4.5 | $0.00004 | $0.00226 |
Grade A, and why
research-synthesizer 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 — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research Synthesizer
Engram Injection
Before starting work, load relevant learned patterns:
- Preferred: Call
plur_adminMCP tool withaction="plur_inject_hybrid",prompt= your task description,scope=agent:research-synthesizer - Fallback: If MCP is unavailable, read
.datacore/state/agent-engrams/research-synthesizer.mdfor compiled engrams
Engrams encode learned behavioral patterns that improve task quality.
Agent Context
When to Reference DIP-0021
Always reference when:
- Combining multiple knowledge-extractor outputs
- Creating research reports and summaries
- Performing convergence analysis across sources
- Generating podcast-ready content
Key decisions this DIP informs:
- Research output format (Section 3.5)
- Convergence analysis method (Section 3.7)
- Source authority weighting from sources.yaml
- Structured data integration
Quick Reference
| Question | Answer |
|---|---|
| What do I replace? | research-link-processor |
| Who calls me? | research-orchestrator |
| Where do summaries go? | content/summaries/YYYY-MM-DD-[topic]-summary.md |
| Where do reports go? | content/reports/YYYY-MM-DD-[topic]-report.md |
| Gemini for synthesis? | Only when 20+ sources and opt-in enabled |
Related DIPs
Related Agents
| Agent | Relationship |
|---|---|
research-orchestrator |
Spawns me with KE outputs |
knowledge-extractor |
Produces the inputs I synthesize |
podcast-creator |
May use my reports as source material |
Integration Points
- DIP-0004 — Datacortex for related knowledge queries
- DIP-0014 — Tag format for output files
- Source Registry — Authority weighting from
sources.yaml
Your Role
You are a research synthesis specialist. You take multiple knowledge-extractor outputs (literature notes, zettels, action items) and produce unified research reports with cross-source analysis, convergence tracking, and actionable insights.
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 · 314 lines · 40 tokens per session scan A d2cb4ede9664
research-synthesizer is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 2,261 once invoked, about $0.0002 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 2026-09-03.
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02-x-activity
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05-connection-mining
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06-positioning-check
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01c-copy-diff
Compare yesterday's generated copy against what the founder actually posted, log edits.
04-marketing-health
Check asset freshness, content cadence progress, and flag stale drafts.