King Context — Documentation Search Skill

Search indexed documentation and research corpora efficiently using .king-context/bin/kctx. Find the right section in ≤3 calls.

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Two Stores, One CLI

King Context keeps two separate stores:

Store	Populated by	What's in it
docs	.king-context/bin/king-scrape <url>	Scraped product/API documentation
research	.king-context/bin/king-research <topic>	Topic-driven research corpora from the open web

Every kctx command is source-aware:

• Default: searches both stores, merged by score.
• --source docs|research scopes to one store.
• --doc <name> scopes to a single doc (works across stores — most precise filter).

Every search/grep hit is prefixed [docs] or [research] so you can tell the source at a glance.

Scraping/research LLM stages can use local Ollama by setting env vars such as ENRICH_PROVIDER=ollama, ENRICH_MODEL=<model>, OLLAMA_API_MODE=openai, and OLLAMA_BASE_URL=http://localhost:11434/v1. For Ollama Cloud/direct native API, use OLLAMA_API_MODE=native, OLLAMA_BASE_URL=https://ollama.com, and OLLAMA_API_KEY. OpenRouter fallback is opt-in with ENABLE_FALLBACK=true plus OPENROUTER_API_KEY.

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Search Strategy

1. Check _learned/                           →  known shortcut?  → .king-context/bin/kctx read <doc> <path>  → DONE
2. .king-context/bin/kctx list               →  which doc + which store?
3. .king-context/bin/kctx search "query"     →  find section     → got it?
4. .king-context/bin/kctx read --preview     →  assess relevance → right section?
5. .king-context/bin/kctx read               →  full content     → DONE
6. Save discovery to _learned/

Rules:

• ALWAYS check _learned/ FIRST — costs ~100 tokens, saves thousands.
• ALWAYS verify learned paths still exist before using them (.king-context/bin/kctx read errors if stale).
• Prefer .king-context/bin/kctx search over .king-context/bin/kctx grep — metadata search is faster and cheaper.
• Use --preview before full read — assess relevance before paying full token cost.
• Use .king-context/bin/kctx grep only for exact code patterns, API names, or error strings.
• Scope aggressively: --doc <name> > --source <store> > unfiltered.
• NEVER read all sections — search narrows, preview confirms, then read only what's needed.

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Picking a Filter (decision tree)

User asks about a specific library/product/SDK?  → --doc <name>
User asks about a research topic you scraped?    → --doc <research-slug>
User asks something generic, unsure which doc?   → --source docs or --source research
User asks "is it anywhere in our indexed stuff?" → no filter (search both)

--doc is the sharpest tool. Run .king-context/bin/kctx list once if you don't know the name.

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Query Decomposition

Transform user intent into efficient CLI queries:

User asks	CLI query
"How to stream audio with ElevenLabs"	.king-context/bin/kctx search "streaming" --doc elevenlabs-api
"Authentication for the Exa API"	.king-context/bin/kctx search "auth api-key" --doc exa
"What does our research say on Chain of Thought"	.king-context/bin/kctx search "chain of thought" --source research
"Compare ToT vs CoT — anything indexed?"	.king-context/bin/kctx search "tree of thoughts" --source research --top 5
"Is rate limiting documented anywhere?"	.king-context/bin/kctx search "rate limit" (both stores)
"Find where Client( is used in httpx"	.king-context/bin/kctx grep "Client\\(" --doc httpx
"What topics does the docs cover"	.king-context/bin/kctx topics elevenlabs-api
"Show only our research corpora"	.king-context/bin/kctx list research

Tips:

• Use 1–2 specific keywords, not full sentences.
• Scope to --doc when you know which doc.
• Use --top 3 to reduce output tokens.
• Keywords match exact terms; use_cases match substrings — "stream" matches "How to stream audio".

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CLI Command Reference

List indexed content

.king-context/bin/kctx list                    # both stores with == Docs == / == Research == headers
.king-context/bin/kctx list docs               # only scraped docs
.king-context/bin/kctx list research           # only research corpora
.king-context/bin/kctx list --json             # JSON (grouped dict when "all", flat list when filtered)

Search by metadata (keywords, use_cases, tags)

.king-context/bin/kctx search "query"                              # cross-store, top 5, merged by score
.king-context/bin/kctx search "streaming" --doc elevenlabs-api     # scoped to a single doc (auto-resolves store)
.king-context/bin/kctx search "reasoning" --source research        # only research corpora
.king-context/bin/kctx search "livecrawl" --source docs            # only scraped docs
.king-context/bin/kctx search "auth" --top 3                       # limit results
.king-context/bin/kctx search "query" --json                       # JSON output

Output tags every hit with [docs] or [research]. Returns title, path, score, first use_case. No content — metadata only.

Read a section

.king-context/bin/kctx read <doc> <section-path>             # full content (auto-finds the store)
.king-context/bin/kctx read <doc> <section-path> --preview   # first ~200 tokens + total estimate
.king-context/bin/kctx read <doc> <section-path> --source research   # force store (rarely needed)
.king-context/bin/kctx read <doc> <section-path> --json      # JSON output

If the doc name isn't unique, pass --source. If section not found, suggests similar paths.

Browse by topic

.king-context/bin/kctx topics <doc>                          # all tags with sections
.king-context/bin/kctx topics <doc> --tag api-reference      # filter to one tag
.king-context/bin/kctx topics <doc> --source research        # disambiguate if needed
.king-context/bin/kctx topics <doc> --json                   # JSON output

Grep content

.king-context/bin/kctx grep "pattern"                        # regex across both stores
.king-context/bin/kctx grep "Client\\(" --doc httpx          # scoped to one doc
.king-context/bin/kctx grep "livecrawl" --source docs        # scoped to docs store
.king-context/bin/kctx grep "pattern" --context 3            # surrounding lines
.king-context/bin/kctx grep "pattern" --json                 # JSON output

Index / re-index

.king-context/bin/kctx index .king-context/data/example.json         # auto-detects via section.source_type
.king-context/bin/kctx index .king-context/data/research/topic.json  # also auto-detected as research
.king-context/bin/kctx index <path> --source research                # force-route to research store
.king-context/bin/kctx index --all                                   # walks data/*.json + data/research/*.json

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Generating New Content

Two producers feed the stores:

# Scrape a product/API doc site → .king-context/docs/<name>/
.king-context/bin/king-scrape https://docs.example.com

# Research a topic from the open web → .king-context/research/<slug>/
.king-context/bin/king-research "prompt engineering techniques" --basic     # 3 queries, no deepening
.king-context/bin/king-research "retrieval augmented generation" --medium   # 5 queries + 1 deepening iteration
.king-context/bin/king-research "mixture of experts" --high                 # 8 + 2 iterations
.king-context/bin/king-research "<topic>" --extrahigh                       # 12 + 3 iterations (most thorough)

Both auto-index on completion — the new doc is immediately searchable via kctx. king-research outputs are tagged source_type: "research" in every section so --source research and the [research] prefix work automatically.

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Self-Learning

After finding a useful section, save a shortcut for future sessions.

When to save

• You found the right section after searching.
• You discovered a gotcha or non-obvious behavior.
• You found a pattern that would help answer similar questions.

How to save

Write to .king-context/_learned/<doc-name>.md:

# <Doc Name> - Learned Shortcuts

## <Topic>
- **<What>** → `<section-path>` section
- Store: docs | research
- Gotcha: <non-obvious behavior>
- Related: `<other-section>` for <reason>

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Last updated: <date>

Tracking the store lets you skip kctx list on the next lookup.

Reading learned shortcuts

Before any search:

1. Read .king-context/_learned/<doc-name>.md.
2. If a shortcut matches the current query, use it directly: .king-context/bin/kctx read <doc> <path>.
3. If the path no longer exists (stale), fall back to normal search and update the learned file.

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Good vs Bad Search Strategies

Good (3 calls, ~400 tokens)

.king-context/bin/kctx search "streaming" --doc elevenlabs-api --top 3
→ 1. [docs] WebSocket Streaming (elevenlabs-api/websocket-streaming) score=8.50

.king-context/bin/kctx read elevenlabs-api websocket-streaming --preview
→ "# WebSocket Streaming\n\nConnect to ws://..." Tokens: 450

.king-context/bin/kctx read elevenlabs-api websocket-streaming
→ Full content

Good (research-scoped, 2 calls)

.king-context/bin/kctx search "zero shot cot" --source research --top 3
→ 1. [research] Zero-Shot CoT (prompt-engineering-techniques/ai-prompt-engineering-...) score=12.50

.king-context/bin/kctx read prompt-engineering-techniques ai-prompt-engineering-patterns-cot-react-tot-zero-shot-cot
→ Full content

Bad (wasteful, ~3000+ tokens)

.king-context/bin/kctx list
.king-context/bin/kctx topics elevenlabs-api
.king-context/bin/kctx read elevenlabs-api getting-started              # wrong section
.king-context/bin/kctx read elevenlabs-api text-to-speech               # still wrong
.king-context/bin/kctx search "websocket streaming audio real-time"     # too many terms
.king-context/bin/kctx read elevenlabs-api websocket-streaming          # finally found it