Wiki Research

Wiki Research — Autonomous Multi-Round Research

You are running an autonomous research loop on a topic, synthesizing what you find, and filing the results into the Obsidian wiki as permanent knowledge.

Before You Start

Writing profile: Before drafting or rewriting natural-language Markdown, read and apply the Writing Profile Resolution section in llm-wiki/SKILL.md. Framework schema, provenance, safety, and operation-specific requirements take precedence. WRITING.md preferences apply only to newly drafted or rewritten natural-language Markdown; preserve source content and structured records.

1. Resolve config — follow the Config Resolution Protocol in llm-wiki/SKILL.md (inline @name override → walk up CWD for .env → global config → prompt setup). This gives OBSIDIAN_VAULT_PATH and OBSIDIAN_LINK_FORMAT (default: wikilink).
2. Read $OBSIDIAN_VAULT_PATH/index.md to understand what's already in the wiki — don't re-research things the wiki covers well
3. Read $OBSIDIAN_VAULT_PATH/hot.md if it exists — it surfaces recent context
4. Check $OBSIDIAN_VAULT_PATH/references/research-config.md if it exists — it may define source preferences, domains to skip, or confidence rules for this vault
5. Check $OBSIDIAN_VAULT_PATH/references/research-backends.md if it exists — it registers optional CLI retrieval backends (social media, video transcripts, paid APIs, etc.). Load any available backends into your working state for this session.

When writing internal links in generated pages, apply the link format from llm-wiki/SKILL.md (Link Format section) using the OBSIDIAN_LINK_FORMAT value.

Confirm the research topic with the user if it's ambiguous. Then proceed.

Research Configuration (optional)

If references/research-config.md exists in the vault, read it and apply any rules it defines:

• Source preferences (e.g., prefer academic sources, avoid certain domains)
• Domains to skip
• Confidence scoring adjustments
• Topic-specific constraints

If the file doesn't exist, proceed with defaults.

Research Backends (optional)

If references/research-backends.md exists in the vault, load it before starting research. It defines zero or more CLI retrieval backends as a YAML list:

backends:
  - name: yt-dlp-transcript      # friendly label
    binary: yt-dlp                # CLI binary (checked with `command -v`)
    invoke: "yt-dlp --skip-download --write-auto-sub --sub-lang en --sub-format json3 -o /tmp/ytvid '{url}'"
    when_to_use: YouTube video URLs, video transcripts
    cost_tier: free               # free | paid
    env_key: ""                   # required env var for paid tiers (empty = always enabled)
    output: text                  # json | text | markdown

  - name: perplexity-sonar
    binary: perplexity
    invoke: "perplexity search '{query}'"
    when_to_use: deep synthesis queries needing multi-source aggregation
    cost_tier: paid
    env_key: PERPLEXITY_API_KEY   # skipped if unset
    output: text

Backend availability check (run once at session start):

• For each backend: command -v <binary> 2>/dev/null — if not found, mark unavailable and note it in the run summary
• For paid backends: also check that $env_key is non-empty — if unset, mark unavailable and note it
• Build a list of active backends (available + key-gated checks pass) to use in Rounds 1–2

Invocation rules (per angle/URL during research):

• Substitute {url} or {query} in the invoke template with the current URL or search query
• Capture stdout; on non-zero exit code → skip this backend for this angle, note the short error, continue
• Fold backend output into the same claims/concepts/entities/contradictions extraction, citing the source URL the backend returns (or the query string for query-mode backends)
• A backend failure never aborts the research run — always fall back to WebSearch/WebFetch

Free-first ordering: Evaluate free backends before paid ones for each angle. If a free backend returns sufficient content, paid backends for the same angle can be skipped.

No research-backends.md → skip this section entirely; behavior is identical to today.

Starter registry template

If the user asks for an example registry, offer this file at $VAULT/references/research-backends.md:

# Optional CLI backends for wiki-research. Delete rows you don't need.
# Skill docs: .skills/wiki-research/SKILL.md — Research Backends section
backends:
  # --- free / local ---
  - name: defuddle-fetch
    binary: defuddle
    invoke: "defuddle '{url}'"
    when_to_use: any URL — cleaner extraction than WebFetch alone
    cost_tier: free
    env_key: ""
    output: markdown

  - name: yt-dlp-transcript
    binary: yt-dlp
    invoke: "yt-dlp --skip-download --write-auto-sub --sub-lang en --sub-format json3 -o /tmp/ytvid '{url}'"
    when_to_use: YouTube video URLs for transcript extraction
    cost_tier: free
    env_key: ""
    output: text

  # --- paid / gated (skipped when env key is unset) ---
  - name: perplexity-sonar
    binary: perplexity
    invoke: "perplexity search '{query}'"
    when_to_use: deep synthesis queries needing multi-source aggregation
    cost_tier: paid
    env_key: PERPLEXITY_API_KEY
    output: text

Round 1 — Broad Survey

Goal: Get a wide map of the topic.

1. Decompose the topic into 3-5 distinct angles (e.g., for "vector databases": what they are, when to use them, leading implementations, trade-offs, production gotchas)
2. For each angle, run 2-3 WebSearch queries using varied phrasing
3. For the top 2-3 results per angle, use WebFetch (or defuddle <url> if available — cleaner extraction) to get content. For each URL, also invoke any active backends whose when_to_use matches (e.g., a YouTube URL triggers yt-dlp-transcript); fold their output into extraction alongside WebFetch results, citing the source URL the backend returns.
4. From each fetched page, extract:
   • Key claims — what the source explicitly states
   • Concepts — ideas, terms, frameworks introduced
   • Entities — tools, people, organizations mentioned
   • Contradictions — places where sources disagree with each other

Track what's covered and what's missing as you go.

Round 2 — Gap Fill

Goal: Close the holes left by Round 1.

Review what Round 1 produced:

• What questions did sources raise but not answer?
• Where do sources contradict each other?
• Which angles got thin coverage?

Run up to 5 targeted searches specifically addressing these gaps. Prefer primary sources, official documentation, and authoritative analyses over link aggregators. For gap-fill queries, also invoke any active query-mode backends (e.g., perplexity-sonar) by substituting {query} in their invoke template — fold results into extraction with backend name as citation context.

Add findings to your working set. Update the contradiction list.