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 commands/datacore-one/datacore/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/commands/datacore-one/datacore/research)<a href="https://agentmods.dev/commands/datacore-one/datacore/research"><img src="https://agentmods.dev/badge/commands/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 | $0.00024 | $0.01064 |
| Opus 5 | $0.00012 | $0.00532 |
| Sonnet 5 | $0.00005 | $0.00213 |
| Haiku 4.5 | $0.00002 | $0.00106 |
Grade A, and why
research 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.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/research Command
Command Context
When to Reference DIP-0021
Always reference when:
- Running research pipelines
- Discovering external sources
- Processing multiple URLs
- Generating research reports and podcasts
Key decisions this DIP informs:
- Research workflow (discover -> select -> process -> synthesize)
- Source registry for available providers
- Output format (summary + report + knowledge + GTD)
- Depth levels (quick/standard/deep)
Quick Reference
| Question | Answer |
|---|---|
| Entry point? | /research <topic|url> |
| Orchestrator? | research-orchestrator |
| Source registry? | .datacore/registry/sources.yaml |
| Settings? | .datacore/settings.yaml (research.*) |
| Output locations? | content/reports/, content/summaries/, 3-knowledge/ |
| What DIPs govern this? | DIP-0021, DIP-0004, DIP-0009 |
Agents This Command Invokes
| Agent | Purpose |
|---|---|
research-orchestrator |
Full pipeline orchestration |
knowledge-extractor |
Per-source content processing (spawned by orchestrator) |
research-synthesizer |
Multi-source synthesis (spawned by orchestrator) |
podcast-creator |
Audio generation (optional, spawned by orchestrator) |
Integration Points
- DIP-0021 - Research architecture
- DIP-0004 - Datacortex for discovery and dedup
- DIP-0009 - GTD action item routing
- Source Registry - Available research sources
Deep multi-source research: discover, gather, process, synthesize, and optionally generate audio.
Usage
/research <topic>
/research <url>
/research --topic "..." --depth quick|standard|deep
/research --podcast --space <space>
Arguments:
| Argument | Description |
|---|---|
<topic> |
Free-text research query (triggers discovery phase) |
<url> |
Specific URL to process (skips discovery) |
--depth |
quick (Perplexity only), standard (default), deep (all sources + Gemini) |
--podcast |
Generate audio overview when done |
--space |
Target space for outputs (default: 0-personal) |
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 · 139 lines · 24 tokens per session scan A dd4e41819853
research is a command published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 1,064 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 commands, from other repositories
prd-review
Review the active PRD with Codex and stream normalized findings to JSONL.
prd-archive
Archive the active PRD (blocked until every accepted finding has a receipt).
prd-map
Build a codebase map so PRDs are written with repo context, not blind.
prd-split
Split the approved PRD into one issue spec per manifest entry.
rca-check
Lint an RCA or premortem document against the canonical template.
prd-os-init
Initialize prd-os in this repo (writes .prd-os/config.json).