Search the web and fetch page contents with Keenable AI — web search, page extraction, point-in-time queries, prompt-driven content extraction. Use when searching the web for current information, fetching webpage contents, extracting specific data from URLs, or researching topics with citations. Triggers on: web search, search the web, fetch page, read URL, find pages about, current information, Keenable, keen search, research with sources, look up, latest news, find information, check online, what is, who is.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Web search and page fetch via Keenable AI — purpose-built for AI agents. Two scripts cover all use cases: search the web, fetch/extract page contents.
Prerequisite: KEENABLE_API_KEY environment variable. Get key at https://app.keenable.ai
--query-time)--prompt)Search cheaply, pick the best results, extract selectively — reduces context by filtering before reasoning.
# Step 1: Search with short snippets to scan titles/descriptions
python3 ~/.claude/skills/keenable/scripts/keenable_search.py "query" --count 10 --snippet-length 200
# Step 2: Pick the 2-3 most relevant URLs from results
# Step 3: Extract only what you need from those URLs
python3 ~/.claude/skills/keenable/scripts/keenable_fetch.py URL --prompt "Extract the key findings"
python3 ~/.claude/skills/keenable/scripts/keenable_search.py "query" [options]
| Quick Example | Purpose |
|---|---|
... keenable_search.py "AI agents 2026" | Basic search |
... keenable_search.py "Claude Code" --site docs.anthropic.com | Site-restricted |
... keenable_search.py "transformer paper" --count 20 | More results |
... keenable_search.py "election results" --published-after 7d | Recent only |
... keenable_search.py "AI safety" --query-time 2026-01-01 | Historical index |
... keenable_search.py "LLM benchmarks" --snippet-length 5000 | Longer snippets |
Key options:
--site DOMAIN — restrict to a specific domain--count N — number of results (1-50, default 10)--snippet-length N — snippet max chars (180-10000)--published-after DATE — filter by publish date (absolute or relative: 7d, 30min, 2h)--published-before DATE — upper bound on publish date--query-time DATETIME — search the index as it stood at this point in time--json — raw JSON output (default: formatted table)python3 ~/.claude/skills/keenable/scripts/keenable_fetch.py URL [options]
| Quick Example | Purpose |
|---|---|
... keenable_fetch.py "https://example.com" | Fetch as markdown |
... keenable_fetch.py URL --live | Force live fetch (not cached) |
... keenable_fetch.py URL --prompt "List all pricing tiers" | Extract specific info |
... keenable_fetch.py URL --max-chars 5000 | Bounded output |
... keenable_fetch.py URL --live --prompt "What is the main argument?" | Live + extract |
Key options:
--live — fetch live page instead of indexed/cached copy--prompt TEXT — LLM-driven extraction (API reads page, returns only what you asked for)--max-chars N — truncate output to N characters--json — raw JSON responsepython3 ~/.claude/skills/keenable/scripts/keenable_setup.py --validate # Test API key
python3 ~/.claude/skills/keenable/scripts/keenable_setup.py --setup-mcp # Add MCP server
| Task | Best Approach |
|---|---|
| General web search | keenable_search.py "query" |
| Search specific site | keenable_search.py "query" --site domain.com |
| Recent news/articles | keenable_search.py "topic" --published-after 7d |
| Historical search | keenable_search.py "query" --query-time 2025-06-01 |
| Read a known URL | keenable_fetch.py URL |
| Extract specific data from URL | keenable_fetch.py URL --prompt "extract X" |
| Fresh content (bypass cache) | keenable_fetch.py URL --live |
| Bounded page read | keenable_fetch.py URL --max-chars 3000 |
| Need | Best Tool | Why |
|---|---|---|
| General web search | Keenable | 100K free/mo, fast, reliable |
| Point-in-time search | Keenable | Only tool that supports historical index queries |
| Extract specific data from URL | Keenable --prompt | API-side LLM extraction, no post-processing |
| Semantic/neural search | Exa | AI-powered relevance ranking |
| Find similar pages | Exa exa_similar.py | Semantic similarity |
| Deep site crawling | Firecrawl | Link following, JS rendering |
| Search + scrape combined | Firecrawl search --scrape | One operation |
| High-volume usage | Keenable | 100K vs Exa 1K vs Firecrawl 500 |
# Find relevant pages
python3 ~/.claude/skills/keenable/scripts/keenable_search.py "React Server Components" --count 5
# Read the most relevant result
python3 ~/.claude/skills/keenable/scripts/keenable_fetch.py "https://react.dev/blog/..." --max-chars 8000
python3 ~/.claude/skills/keenable/scripts/keenable_fetch.py "https://example.com/pricing" \
--prompt "List all pricing tiers with name, price, and features as a markdown table"
python3 ~/.claude/skills/keenable/scripts/keenable_search.py "AI regulation" \
--published-after 2026-01-01 --published-before 2026-06-01 --count 20
For native tool access without scripts, add Keenable as an MCP server:
claude mcp add keenable \
--transport http https://api.keenable.ai/mcp \
--scope user \
--header "X-API-Key: $KEENABLE_API_KEY"
| Problem | Fix |
|---|---|
KEENABLE_API_KEY not set | Export in ~/.config/env/secrets.env or shell profile |
401 Unauthorized | Check key starts with keen_ and is valid |
429 Rate Limited | Authenticated: per-org limits. Unauthenticated: 1K/hr shared |
| Stale results | Use --live flag on fetch, or remove --query-time from search |
| Truncated content | Increase --max-chars or --snippet-length |
| Error fetching URL (404/422) | URL may not be indexed — add --live to fetch any URL |
| File | Contents |
|---|---|
references/api-reference.md | Full API parameter reference for both endpoints |
references/selection-guide.md | Detailed comparison with Exa and Firecrawl |
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Search academic papers, build literature reviews, and synthesize research findings — combines Exa MCP (research_paper category, arxiv filtering) with arxiv-mcp-server for paper discovery, download, and deep analysis. Triggers on academic paper, literature review, research synthesis, arxiv, find papers, scholarly search.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when creating, auditing, or maintaining AGENTS.md files and Codex CLI configuration for any project—including initializing AGENTS.md for cross-agent compatibility (Codex, Cursor, Copilot, Devin, Jules, Amp, Gemini CLI), generating config.toml or .rules files, scaffolding .agents/skills/, converting CLAUDE.md to AGENTS.md, or auditing existing agent configs for bloat and staleness. Complementary to codex-orchestrator (which executes subagents; this skill creates the config files they consume).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Academic research skill for Biblical Hebrew, Semitic linguistics, cuneiform studies, and comparative Ancient Near Eastern research. Provides Sefaria API for Hebrew Bible, CDLI/ORACC for cuneiform databases, and web discovery via Omnisearch, Exa, Firecrawl, and Obscura for finding scholarly sources across JSTOR, Perseus, Persée, Google Scholar, and academia.edu. Triggers on Hebrew quotes, cuneiform, Sefaria, ANE research, Minoan, search for scholarship, find papers, literature review, scholarly search, academic search, Genesis/Tehom, Ugaritic, Talmudic sources, extract from PDF, OCR academic.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build comprehensive ARCHITECTURE.md files following matklad's canonical guidelines — bird's-eye views, ASCII/Mermaid diagrams, codemaps, invariants, and layer boundaries. Triggers on document the architecture, create ARCHITECTURE.md, map this codebase, architectural overview.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate physically-based atmospheric scattering shaders — sky domes, planetary atmospheres, LUT-optimized pipelines, depth-aware post-processing. Four modes — sky-dome, atmosphere-post, planet, lut. Triggers on atmospheric scattering, sky shader, sunset rendering, planet atmosphere, Rayleigh scattering, Mie scattering, volumetric sky, sky dome, atmosphere post-processing, aerial perspective, transmittance LUT, sky rendering, realistic sky, planetary rendering.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.