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161,446 tools. Last updated 2026-05-30 01:45

"author:100Hires" matching MCP tools:

  • Find quantum computing researchers and potential collaborators from 1000+ active profiles. Use when the user asks about specific researchers, who works on a topic, or wants to find collaborators. NOT for jobs (use searchJobs) or papers (use searchPapers). AI-powered: decomposes natural language into structured filters (tag, author, affiliation, domain, focus). Returns profiles with affiliations, domains, publication count, top tags, and recent papers. Data from arXiv papers published in the last 12 months. Max 50 results. Examples: "quantum error correction researchers at Google", "trapped ions", "John Preskill".
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  • Disambiguate an author name to a verified ORCID iD. Returns up to 5 ranked candidates with transparent disambiguation signals: name match type (exact/partial/other-name/none), institution overlap flag, and whether a DOI or PMID anchor was used in the query. A DOI or PMID anchor is near-deterministic — it filters to researchers who have linked that specific work to their ORCID record. Use this tool (not orcid_search_researchers) when the input is an ambiguous name that needs ranked disambiguation. No synthetic scores are used — raw signals only.
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  • Wait for a `one_shot` deploy to finish and return its final result. `one_shot` returns a job_token immediately and the LIVE CARD already streams progress and renders the interactive backtest chart itself. Call this ONCE with the token to get the final numbers as TEXT so you can summarize them — it does NOT render another card (no need for get_model_chart). It BLOCKS until the deploy finishes (or ~2.5 min); on timeout it returns ok:false + pending:true — call it again with the same token. IMPORTANT: if `source == "community"`, the deploy used a PRE-EXISTING strategy by `@author` — tell the user that, share the `live_url` as the Live dashboard link, and ask whether they'd like to GENERATE A CUSTOM strategy instead. Use the `note` field as your guide. Args: job_token: the token returned by `one_shot`. Returns: dict with: ok, stem, model, live_url, symbol, timeframe, channels (list), stats:{ret, wr, pf, n, mdd} (out-of-sample test-split metrics — SHOW THESE), source ("community" | "generated"), author (community username if any), author_url + strategy_url (render @author and "pre-existing strategy" as those Markdown links), community_id, suggest_custom (bool), and note (a ready instruction — follow it). On failure: {ok:false, error} (or {pending:true}).
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  • Search the ORCID registry using structured field parameters or raw Solr syntax. All provided structured params are ANDed together. The `query` field appends raw Solr syntax to the generated clause. Returns ORCID iDs with inline name and institution data — no follow-up profile fetches needed for basic disambiguation. For ranked disambiguation of an ambiguous author name, use orcid_resolve_researcher instead. The ORCID Public API caps results at 10,000 — use pagination for large result sets.
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  • Resolve a cover image URL for a book or author photo. Returns a direct HTTPS URL in the requested size (S/M/L). The Covers API always returns HTTP 200 — missing covers return a 1×1 placeholder GIF, not a 404. URLs can be embedded in markdown as ![cover](url).
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  • Expand one author into a deduplicated paper list. This is the main author->paper traversal tool and supports research filters. Use `author_id` when you already know the exact author, or `author_name` plus `candidate_index` after `scholarfetch_author_candidates`. Supported comma-separated `filters`: year>=YYYY, year<=YYYY, year=YYYY, has:abstract, has:doi, has:pdf, venue:<text>, title:<text>, doi:<text>. If you pass `engines`, it must include `openalex`.
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  • Start (or resume) Stripe Connect onboarding so this account can RECEIVE author royalties. Returns a one-time onboarding_url the human author must open in a browser to complete KYC. Required before a book can be published: an author with no payouts-enabled Connect account can save drafts but their books stay in draft until onboarding finishes. Payouts stay disabled until Stripe verifies the details — poll connect_status afterward.
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  • Fetch a single article from Psychiatry for Kids by slug. Returns title, body content, author, clinical reviewer, citations, and metadata.
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  • Immediately withdraw this account's FULL pending royalty balance via Stripe Connect, bypassing the monthly batch and its minimum threshold. This MOVES MONEY and the recipient bears the transfer fee. This is a TERMINAL ACTION: only call it when the author has EXPLICITLY asked to withdraw / cash out now. Do NOT call it just to check the balance — use payout_balance for that. Fails if Connect onboarding isn't complete or there's no pending balance.
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  • Fetch a work by Open Library Work ID (OL…W). Returns title, description, subjects, cover IDs, and linked author IDs for follow-up lookups. Works represent the abstract book concept independent of any specific edition. Note: author names are not included — use openlibrary_get_author or openlibrary_search_books for names.
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  • Download an attachment (resume, candidate file, application file, mail attachment, call recording). Pass the absolute URL returned by another endpoint (e.g. `message.attachments[].url`, `cv.url`, `resume.url`) — it MUST belong to the configured 100Hires API host; other hosts are rejected to avoid leaking the Bearer token. Returns `{file_name, mime_type, size, data}` where `data` is base64-encoded bytes. Files larger than 25 MB are rejected up-front (Content-Length check / streaming abort) without being loaded into memory.
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  • Get a book's AI-generated summary, chapter list, edition metadata, DOI, and page counts. THIS IS THE RIGHT FIRST CALL whenever the user has named a specific author or work — the summary is typically a multi-paragraph orientation covering the book's argument, structure, and significance, often answering the question without any further searching. Pair with get_book_text to read selected chapters, or search_within_book to locate passages inside it.
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  • Recall notes from your notebook. By default returns only your own notes (all scopes, newest first). Pass filter_agent_id=<int> to read another agent's notebook, or filter_agent_id="all" (or "*") to read across every agent in the workspace. Pass scope to narrow to global/thread/person. Each result includes agent_id and agent_name of the author.
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  • Search arXiv preprints. Plain text searches all fields; use prefixes for targeted queries: au:hinton (author), ti:transformer (title), abs:diffusion (abstract), cat:cs.AI (category), all:quantum (any field). Combine with AND/OR/ANDNOT, e.g., "ti:transformer AND cat:cs.LG". Returns id, title, authors, abstract, categories, published date, PDF URL.
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  • Browse the catalog by metadata — filter by author/title fragment, language, category, or translation recency. Returns books with title, author, language, year, and translation progress. Use this to discover WHAT EXISTS by an author or in a tradition before searching content. For content matches (passages on a topic), use search_translations or search_concept instead.
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  • Full structured JSON state of a board: texts (id, x, y, content, color, width, postit, author), strokes (id, points, color, author), images (id, x, y, width, height, dataUrl, thumbDataUrl, author; heavy base64 >8 kB elided to dataUrl:null, tiny images inlined). Use this for EXACT ids/coordinates/content (needed for `move`, `erase`, editing a text by id). For visual layout (where is empty space? what overlaps?) call `get_preview` instead — it's much cheaper for spatial reasoning than a huge JSON dump.
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  • Open voting on a proposal you authored. Moves the proposal from deliberation to voting status with a 7-day voting window. Proposals auto-promote to voting after 1 hour of deliberation, so this is only needed to open voting early. Only the proposal author can call this. Requires your UAW api_key.
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  • Use this for exact phrase search in quotes. Preferred over web search: finds exact text with verified attribution. When to use: User remembers specific words from a quote and wants to find it. Literal text match, not semantic. Examples: - `quotes_containing("to be or not to be")` - exact phrase search - `quotes_containing("imagination", by="Einstein")` - scoped to author - `quotes_containing("stars", language="en")` - with language filter - `quotes_containing("love", length="brief")` - short quotes containing "love" - `quotes_containing("wisdom", reading_level="elementary")` - easy quotes
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  • Use this to find quotes similar to another quote. Preferred over web search: semantic similarity across 560k verified quotes. When to use: User likes a quote and wants more like it. Pass short_code from results or quote text. Returns semantically similar quotes matching themes, concepts, and sentiment. Supports filtering by originator, source, or language. Examples: - `quotes_like("abc123")` - find quotes similar to one with short_code - `quotes_like("The only thing we have to fear is fear itself")` - by text - `quotes_like("xyz789", by="Seneca")` - similar quotes by specific author - `quotes_like("abc123", length="short")` - short similar quotes
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