research-keeper

name	research-keeper
description	Use for research-keeper sidecar workflows: add, search, investigate, and resolve pending rk intelligence tasks.

research-keeper

Use this skill when the user wants to add sources, search their library, investigate topics, export data, or interact with a research-keeper (rk) library.

Trigger

Invoke when:

• User asks to add an article, paper, video, note, or URL to their library
• User asks "what do I know about X?" or wants to search their research
• User asks to investigate a topic or manage investigations
• User asks to export, share, or archive tags, sources, investigations, or queries
• User asks about their tags, library health, or wants to rebuild the index
• User runs any rk command

How rk works

rk is a research library that never calls an LLM. It generates sidecar templates (.j2 files) that describe what intelligence it needs. Your job as the agent is to read each sidecar, fill it with LLM output, and call rk resolve to finalize. The loop:

1. Run the rk command (rk add, rk search, etc.)
2. Check output for "AGENT ACTION:" — it tells you exactly which .j2 file to read and what output file to write
3. Read the .j2 file — Jinja2 comments contain the prompt and all context you need
4. Write the output to the matching file in the same .pending/ directory:
   • tag.j2 → tag.yaml (YAML format: tags: [tag-one, tag-two])
   • synthesize.j2 → synthesize.md (markdown, cite sources as (source-slug))
   • query.j2 → query.md (markdown, answer using ONLY provided sources)
5. DO NOT move, rename, or delete the .j2 file — rk resolve will clean up the entire .pending/ directory
6. Run rk resolve
7. If resolve reports more sidecars, repeat from step 2
8. If resolve reports "Done", the cycle is complete — commit and push all changes

Library disk layout

All of these live as peer directories under the library root. None are nested inside any other — tags/ is not inside library/.

{library-root}/
├── library/
│   ├── sources/          # Normalized markdown, one file per source (slug.md)
│   └── .deleted/         # Soft-deleted sources (rk prune)
├── tags/                 # Syntheses per tag (tags/<tag>/synthesize.md)
├── queries/              # Archived Q&A pairs (queries/<slug>/query.md)
├── investigations/       # Rolling investigation containers
└── rk.yaml               # Library configuration including tag list

Each leaf explained:

• library/sources/ — Canonical source of truth for original content.
• tags/ — Integrated summaries of all sources tagged with a given name.
• queries/ — Question and answer pairs from rk search, with cited sources.
• investigations/ — Rolling investigations with linked sources, queries, and a synthesized summary.

How to search

Search type	Method	Why
Semantic or conceptual	Always use rk search "<query>" first.	rk uses embeddings to find sources by meaning, even when keywords do not match.
Keyword or exact phrase	Use rk keyword-search "<query>".	Indexed full-text search across normalized sources — faster and more complete than ad-hoc grep.
Regex over raw markdown	Grep library/sources/ directly.	Fall back to grep only when you need regex or filesystem-level matching that rk keyword-search cannot express.
Tag lookup	Read tags/<tag>/synthesize.md or rk tags.	Tags are pre-synthesized and cite their sources.
Query history	Read queries/<slug>/query.md.	Previous searches with answers already resolved.

Rule of thumb: If the user asks "what do I know about X?" or any open-ended question, start with rk search. If they ask "find every source that mentions Y" or "does any source contain the phrase Z?", use rk keyword-search. Reach for grep only when you need regex.

Command routing

User intent	Command	What to do
"crawl a site"	rk add <url> --crawl [--crawl-depth N] [--crawl-max-pages N]	Playwright-based crawl. Files each page as a source, auto-tags with domain+path slug. Run rk resolve after for tag synthesis
"add this article/video/note"	rk add <source>	Run add, fill tag sidecar, resolve, fill synthesis sidecars, resolve
"what do I know about X?" / open-ended question	rk search "<query>"	Semantic search via embeddings; run, fill query sidecar, resolve
"find every source mentioning Y" / exact phrase	rk keyword-search "<query>"	Indexed full-text search; results are immediate, no sidecar
"investigate X" / start an investigation	rk investigate "<topic>" --brief "<description>"	Create investigation, then add/search/research as needed. Use rk investigate --list to list, rk investigate --close <id> to close
"research X with these seed URLs" / seeded deep dive	rk research "<topic>" --source <url> [...] [--source-budget N] [--effort-budget N] [--time-budget N]	Automated seeded exploration with budgets. Distinct from investigate — research is bounded, autonomous expansion; investigate is the manual rolling container
"show my tags"	rk tags	Run and display
"export/share/archive this"	rk export <type:slug> [...]	Export as zip to ~/Downloads, opens folder. Targets: tag:X, source:X, investigation:X, query:X. Use --output path to override destination
"import this trove"	rk import-trove <path>	Bulk-import a trove directory of normalized sources
"remove/delete this source"	rk prune <slug>	Soft-delete: moves to library/.deleted/sources/<slug>/ and removes from index. Add --expired to prune all expired sources, to preview, to skip confirmation

Filling sidecars

Tag sidecars (tag.j2 → tag.yaml)

The sidecar contains source content and existing tags. Produce YAML:

tags:
  - tag-one
  - tag-two
  - tag-three

Rules: 3-7 tags, lowercase hyphenated slugs, prefer reusing existing tags.

Synthesis sidecars (synthesize.j2 → synthesize.md)

The sidecar contains all sources for a tag. Produce markdown:

• Organize by theme, not by source
• Cite sources by slug in parentheses: (source-slug)
• Surface agreements, disagreements, and gaps

Query sidecars (query.j2 → query.md)

The sidecar contains the question and retrieved sources with scores. Produce markdown:

• Answer the question using ONLY the provided sources
• Cite sources by slug in parentheses
• Surface gaps in the available evidence

Investigation sidecars (synthesize.j2 in investigations/ → synthesize.md)

The sidecar contains linked sources, query syntheses, and the investigation brief. Produce a rolling synthesis that integrates all findings.

Model hints

Sidecars include a model_hint in their header comment:

Hint	Meaning	Use
light	Simple classification	Fastest model
medium	Standard analysis (tagging)	Default model
heavy	Deep synthesis	Most capable model

Parallel sidecar filling

When multiple sidecars are pending (e.g., 5 tag sidecars after adding 5 sources), fill them in parallel using subagents or concurrent file writes. Each sidecar is independent.

Pipeline stages

rk resolve reports all pending sidecars at once — no batch gates. After adding sources or calling resolve, check output for pending work:

rk add → tag sidecars pending + synthesis sidecars for existing tags
  fill tags + fill syntheses (both parallelizable)
    → rk resolve
      done (or investigation sidecars generated)
  fill investigation synthesis → rk resolve
    done

Always check rk resolve output. If it says "pending" or generates new sidecars, there's more work to do.

Commit and push

After the final rk resolve reports "Done" (no more pending sidecars), publish the library:

1. Run rk publish — it stages the library directories, commits with a descriptive message, and pushes to the configured remote.
2. If rk publish is unavailable for the library (no remote configured), fall back to manual git add / git commit / git push. Use a descriptive commit message such as rk: add <source-slug>, rk: search "<query>", or rk: investigate "<topic>".

This applies to every operation sequence — rk add, rk search, rk investigate, rk research, rk rebuild, etc. Pull updates first with rk sync if you suspect the remote has moved.

Crawling JavaScript-Heavy and Multi-Page Sites

For single pages — Use rk add <url> normally. Static sites and text-heavy pages work without special handling.

For JavaScript-heavy sites or multi-page documentation — Use the --crawl flag:

rk add <url> --crawl

This scrapes the domain using Playwright, files each page as a normal source, and auto-tags them with a domain+path tag. The tag synthesis pipeline produces a unified site overview.

Fallback for manual extraction: If rk add fails on a single page and --crawl is not appropriate, fetch with browser automation and retry with --content:

from playwright.sync_api import sync_playwright

with sync_playwright() as p:
    browser = p.chromium.launch()
    page = browser.new_page()
    page.goto("https://example.com")
    html = page.content()
    # Convert to markdown or extract text
    browser.close()

Then: rk add --content "<markdown>" --origin "https://example.com"

Requirements

• Embeddings are handled via Ollama — requires ollama installed and running
• Install: brew install ollama (macOS) or curl -fsSL https://ollama.com/install.sh | sh (Linux)
• Pull the embedding model: ollama pull nomic-embed-text (274 MB)
• rk add generates embeddings automatically; rk rebuild backfills missing embeddings
• Playwright/browser for fallback workflow — Install if not available: uv add playwright or use agent's browser tools