Search AO3 for works. All filters optional; combine freely.

RECOMMENDATION WORKFLOW — reading before recommending is MANDATORY, and the reading is done by a SEPARATE model, not you. Blurbs are author-written ads; never recommend, rank, or summarize a fic from its blurb alone. Cast a wide net (pages=2-3, i.e. 40-60 blurbs), shortlist the promising ones, then hand the top ≤20 ids to read_works — a second AI reads them and reports back. Recommend ONLY fics that came back from read_works. Do not read fic text yourself; delegating it is the entire point of this server.

SEARCH STRATEGY — searching is cheap and reading is delegated, so the winning move is always to OVER-FETCH and let read_works brute-force the shortlist, never to craft one perfect narrow query. Filters multiply: each one you add cuts the pool, and stacked filters routinely cut it to zero.

USE WILDCARDS LIBERALLY — abuse them. A * matches any run of characters and works in EVERY name field (fandom, relationship, character, tags) and in query. Wrapping a term in stars is the single best defence against AO3's exact-canonical-name trap: fandom="Genshin Impact (Video Game)" returns ZERO (the canonical tag is actually "原神 | Genshin Impact (Video Game)"), but fandom="*Genshin Impact*" returns the whole fandom. Likewise relationship="*Kazuha*Scaramouche*", tags="*Enemies to Lovers*". When you don't know the exact canonical name — which is most of the time — reach for a wildcard first instead of guessing the literal string.

IF YOU GET 0 (or few) RESULTS, that is almost always your query being too narrow, NOT the content missing from AO3. Recover instead of giving up:

• FIRST, wildcard the name fields (*Genshin Impact*). This fixes the most common cause — an exact-match field that didn't match the canonical tag — in one retry, without a separate find_tags round-trip.

• Still unsure of a name? find_tags resolves it, or move the idea into query as free text (fuzzy, no canonical spelling needed).

• Drop filters one at a time and retry: word_count first, then complete_only, then rating. Re-add only what the user insisted on.

• Concepts don't need to be tags at all: "slow burn rivals in a bakery" works fine as free-text query even if no such tag exists.

• Still thin? Search the broad version (fandom + category, sort by kudos), fetch 2-3 pages, and let the blurbs + read_works do the filtering. A human reader has to search narrowly because they can only read a few fics; you can read twenty at once, so breadth costs you nothing.

Results show numeric work ids, not URLs. When relaying a work to the user, build the link yourself: https://archiveofourown.org/works/{id}

Each result shows a kudos-to-hits ratio (k/h) — AO3's most honest quality proxy, since kudos are one-per-reader but hits count every visit. Compare it only within similar works: multi-chapter fics accumulate hits on every chapter visit, so long WIPs run structurally lower ratios than one-shots.

Args: query: free-text search. Supports AO3's full operator syntax (case-sensitive, space after colon required where shown): "exact phrase", AND / OR / NOT, -term to exclude; words>10000, words:1000-5000, kudos>500 (same for hits/ comments/bookmarks); sort:kudos, sort:hits, sort:>posted (oldest first); otp: true (exactly one ship, no side pairings); creators: username / -creators: username; summary: "phrase"; expected_number_of_chapters: 1 (one-shots only); series.title: * (part of a series); language_id: en. Also supports * wildcards, e.g. *coffee shop*. ⚠️ query is a FULL-TEXT match on the fic body, AND'd with every other filter — so it narrows HARD. Do NOT stuff mood/concept synonyms here ("nuzzle OR forehead kiss OR won't let go"): that demands the prose literally contain one of those strings on top of your tag/fandom filters, and routinely collapses a healthy 60-result search to 0. Concepts belong in tags (wildcarded), not here. Use query for author names, quoted title/summary phrases, or the numeric operators above — leave it EMPTY when a tag already covers the vibe. title: words in the work title. author: author/creator name. fandom: fandom name, e.g. "Naruto" (comma-separate several). Exact canonical match — but * wildcards work here: prefer "Genshin Impact" over the literal name to survive canonical tags with prefixes/aliases (e.g. "原神 | Genshin Impact (Video Game)"). relationship: ship tag. Format: "A/B" romantic, "A & B" platonic, canonical name order, e.g. "Kakashi Hatake/Iruka Umino". Wildcards work: "KazuhaScaramouche*" beats guessing the exact tag order. character: character name(s), comma-separated. Wildcards work here too. tags: freeform tags, comma-separated, EXACT canonical spelling (use find_tags to resolve, or wildcard it: "Enemies to Lovers"). Popular canonical tags: Fluff; Angst; Hurt/Comfort; Emotional Hurt/Comfort; Angst with a Happy Ending; Hurt No Comfort; Enemies to Lovers; Friends to Lovers; Enemies to Friends to Lovers; Slow Burn; Mutual Pining; Fake/Pretend Relationship; There Was Only One Bed; Idiots in Love; Getting Together; Established Relationship; First Kiss; Found Family; Fix-It; Time Travel; Kid Fic; Domestic Fluff; Tooth-Rotting Fluff; Crack; Crack Treated Seriously; 5+1 Things; POV Outsider; Soulmates; Smut; Plot What Plot/Porn Without Plot; Alpha/Beta/Omega Dynamics; Dead Dove: Do Not Eat; Canon Compliant; Post-Canon; Alternate Universe - Modern Setting; Alternate Universe - Canon Divergence; Alternate Universe - Coffee Shops & Cafés; Alternate Universe - College/University; Alternate Universe - Soulmates. rating: one of: general, teen, mature, explicit, not rated. categories: comma-separated relationship categories to include: F/F, F/M, Gen, M/M, Multi, Other. Empty = all. complete_only: only finished works. word_count: range like "10000-50000", ">5000" or "<20000". sort_by: relevance | kudos | hits | comments | bookmarks | words | date_updated | date_posted. page: which result page to start from (for paging through results). pages: result pages to fetch, 20 works each (1-5). For a targeted lookup 1 is enough; for a recommendation hunt fetch 2-3 pages (40-60 blurbs) so the read_works shortlist has real competition.

Resolve fuzzy wording to canonical AO3 tag names (live autocomplete).

Use before search_works when unsure of exact spelling — e.g. "coffee shop" resolves to "Alternate Universe - Coffee Shops & Cafés".

Args: term: partial/fuzzy tag text, e.g. "enemies to", "coffee", "kakashi". kind: what to complete: tag | fandom | relationship | character.

Get the full metadata card for one work: tags, stats, summary, series info.

Args: work_id: the numeric AO3 work id (from search results or a URL like archiveofourown.org/works/12345).

Have the mini reader (a separate AI) read full fics and report on each.

Works for a single fic or up to 20 at once. You never receive fic text — only structured reader reports, one per work. The reader answers your query directly (anything works: "is the ending happy?", "how explicit is it?", "which of these should I read first?") plus gives a general digest of plot, characters, style, and content notes. When given several fics, it ends with a comparison section ranking them against your query.

This is the ONLY approved way to read a fic. A separate model does the reading so a whole novel never touches your context. You MUST send fics here before you recommend, rank, summarize, or judge them — search blurbs are not enough, and reading raw text yourself defeats the entire point of this server. Shortlist from blurbs, read here, then recommend.

Reading depth: a single-fic call sends the reader up to ~150k words (whole novels fit); in a batch each fic is capped at ~100k characters. If a long fic's report matters, read it alone. Batches that exceed the token budget are split internally, then a final reduce pass still produces ONE global comparison across the whole batch.

Content refusals: the reader is Gemini, which has a non-configurable safety filter that occasionally refuses explicit or extreme fics — that fic's report comes back as "(mini reader returned no text …)". The server already retries once on the backup model, but the block is intermittent, so if a fic you care about is refused: read it ALONE (a single fic isn't dragged down by an extreme one sharing its batch), or just retry. In a mixed batch, one refused fic does not sink the others — their reports still return.

Args: work_ids: 1-20 numeric AO3 work ids (from search results or URLs). query: the question to answer about each fic.

⚠️ NOT RECOMMENDED — escape hatch only. Returns the raw full text of ONE fic directly to you, bypassing the mini reader.

Prefer read_works in almost every case. A fic can run 150k+ words; pulling that into your own context buries everything else, burns your tokens, and throws away the whole reason this server exists — delegating reading to a cheap second model. read_works hands you a structured report plus verbatim prose samples, which is enough to judge, compare, and recommend a fic without the fic ever entering your context.

Only reach for this when you genuinely need exact wording a report can't carry — e.g. the user explicitly asks you to quote or close-read a specific passage. If you just want to know what a fic is like or whether it's good: use read_works instead.

Args: work_id: the numeric AO3 work id. max_words: cap the text to the first N words (0 = whole fic). Set a limit to sample a fic's opening instead of dumping the entire thing into your context — a few thousand words is usually plenty to judge voice.