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 skills/datacore-one/datacore/researchnpx skills add datacore-one/datacore --skill researchgit 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/skills/datacore-one/datacore/research)<a href="https://agentmods.dev/skills/datacore-one/datacore/research"><img src="https://agentmods.dev/badge/skills/datacore-one/datacore/research.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 | $0.00019 | $0.00328 |
| Opus 5 | $0.00010 | $0.00164 |
| Sonnet 5 | $0.00004 | $0.00066 |
| Haiku 4.5 | $0.00002 | $0.00033 |
Grade A, and why
Research for Datacore 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 today.
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.
What it actually says
Research for Datacore
Automated research processing — curate links, generate NotebookLM podcasts, extract knowledge artifacts, and build industry landscapes.
Tagline: "Curate links. Wake up to podcasts and insights."
What This Module Provides
Tools (MCP):
datacore.research.queue— List pending research links and processing statusdatacore.research.sources— Manage and query research source registry
Skills:
- Research status checking
- Ad-hoc podcast creation
Agents:
research-orchestrator— Full pipeline orchestration (DIP-0021)podcast-creator— NotebookLM podcast generation
Commands:
/research-daily— Manually trigger daily research processing
When to Use
Triggers: research, podcast, readwise, sources, literature, zettel, notebooklm.
What ships with it
23 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .gitignore 122 B
- agents/podcast-creator.md 1.1 KB
- agents/research-orchestrator.md 2.1 KB
- CLAUDE.base.md 6.5 KB
- commands/create-podcast.md 7.1 KB
- commands/nightshift-hook.md 5.1 KB
- commands/research-daily.md 6.0 KB
- commands/research-status.md 12 KB
- commands/today-hook.md 3.9 KB
- docs/pipeline-podcasts.md 5.9 KB
- lib/__init__.py 26 B runs code
- lib/adapters/__init__.py 96 B runs code
- lib/adapters/readwise.py 8.1 KB runs code
- lib/nlm_auth_sync.py 8.0 KB runs code
- lib/research_orchestrator.py 49 KB runs code
- lib/research_router.py 13 KB runs code
- lib/sync_state.py 2.8 KB runs code
- module.yaml 3.1 KB
- README.md 3.6 KB
- requirements.txt 784 B
- skills/create-podcast/SKILL.md 416 B
- skills/research-status/SKILL.md 716 B
- tools/index.js 5.5 KB runs code
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.
- today First seen · 47 lines · 19 tokens per session scan A d448f9a6b72b
Research for Datacore is a skill published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 328 once invoked, about $0.0001 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.
Other skills, from other repositories
learn-from-correction
Propose a principle edit to a skill or persona file based on a (agentoutput, humanoutput) correction pair. Outputs a proposal markdown for human review - never auto-edits the target file.
research-mode
Anti-hallucination research mode. Toggle on to enforce citation requirements, source grounding, and "I don't know" behavior. Toggle off for creative work.
council
Multi-persona debate for founder decisions. 4 personas argue a topic across structured rounds.
fable-discipline
Engineering discipline distilled from a forensic read of one model's work. Use when building a feature, fixing a bug, writing tests, hardening a data path, or running any task that spans multiple files, sources, or sessions. Two layers: how to RUN the task (stage it, verify each stage with a check that can fail, write…
add-editor
Wire Deus's memory + evolution layers into an external code editor (Zed and other ACP/MCP clients) so the editor's own agent gains Deus's vault recall and self-improving reflexion loop. Configuration only — no new code. Triggers on "add editor", "use Deus in my editor", "zed integration", "editor integration", "wire…
add-llama-cpp
Install and verify a local llama.cpp server for optional Deus local-generation experiments. Keeps Ollama as the required default for embeddings and judge work.