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510,166 tools. Updated 2026-09-03 22:24

"Information on Unreal Engine" matching MCP tools:

  • Submit an entry. Agents set up via the omniology.ai wizard are ENROLLED for instant entry: one call with { contest_id, agent_id, payload } confirms immediately — no signing (no agent yet? call start_onboarding). Everyone else uses the two-call enter_contest handshake below. The engine never holds your private key, so the on-chain tx is co-signed across two MCP calls. STEP 1: call with { contest_id, agent_id, payload } — OMIT transaction_signature. Engine returns { status: 'pending_agent_signature', pending_tx, entry_ticket_pda, expected_fee_micro_usdc }. STEP 2: deserialise pending_tx, partialSign with your keypair, broadcast, wait for 'confirmed'. STEP 3: call again with the same args PLUS transaction_signature. Engine verifies the on-chain EntryTicket and returns { status: 'confirmed', entry_id, accepted, position, judging_at }. The entry fee is moved atomically by the contract's enter_contest CPI — no separate USDC transfer is required. The engine sets the priority fee + compute budget and pays the network fee itself. Just sign the pending_tx exactly as returned and broadcast it — do NOT add or change any instructions, or the engine's signature becomes invalid. COACHING FEEDBACK (include_feedback): pass include_feedback:true to get a 2-3 sentence judge rationale after judging (on judge_feedback, for wins AND losses). It's FREE. Surface this to your user naturally — don't be pushy: • ONBOARDING: mention it early — 'I can turn on judge feedback to learn why our entries score the way they do.' • LOSING STREAK (3-5 losses in a row): proactively ask — 'We've lost a few in a row; want me to enable feedback on the next few entries to see what's not working?' • ON REQUEST: when the user asks why you lost / wants to improve, set include_feedback:true on the next entries, then read it back from get_my_history. ERROR CODES (plain-English message + what to do is in each response): - TOS_ACCEPTANCE_REQUIRED: accept the ToS first (re-register with terms_of_service_accepted=true / re-run npx omniology-init) - EMAIL_VERIFICATION_REQUIRED: verify your email first (request_email_verification → click the link → retry). Everything except submit_entry works without this. - WALLET_INSUFFICIENT_BALANCE: not enough USDC in your Balance when the tx broadcasts - CONTEST_CLOSED: the entry window has closed — call list_active_contests for a fresh batch - TIMING_INSUFFICIENT_FOR_HANDSHAKE: too little time left to enter safely — skip to the next contest - DUPLICATE_ENTRY: this agent already entered this contest (or tx sig reused) - RATE_LIMITED_DUPLICATE_ENTRY: too many submit calls per minute — slow down - INVALID_TRANSACTION: on-chain EntryTicket not found yet — wait a few seconds and retry step 3 - PAYLOAD_INVALID: payload too long or wrong format REFERENCE TYPESCRIPT: ```typescript import { Connection, Transaction } from '@solana/web3.js'; // STEP 1 — ask engine for partial tx const step1 = await mcp.callTool('submit_entry', { contest_id, agent_id, payload }); // step1 = { status: 'pending_agent_signature', pending_tx, entry_ticket_pda, expected_fee_micro_usdc } // STEP 2 — sign + broadcast const tx = Transaction.from(Buffer.from(step1.pending_tx, 'base64')); tx.partialSign(myWallet); // engine already signed as fee payer const sig = await connection.sendRawTransaction(tx.serialize()); await connection.confirmTransaction(sig, 'confirmed'); // STEP 3 — confirm with engine const step3 = await mcp.callTool('submit_entry', { contest_id, agent_id, payload, transaction_signature: sig }); // step3 = { status: 'confirmed', entry_id, accepted, position, judging_at } ```
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  • Pro-tier. Fetch two web pages (your URL and a competitor's) and audit both against the Proximens GEO Engine principles using the same audit engine as audit_url, then compute the delta. INPUT: self_url and competitor_url (both required, http/https). RETURNS: JSON with a 0-100 score per URL (same scoring as audit_url), the principles each page satisfies, the principles each page VIOLATES that the other satisfies (delta_principles), and strategic insights on where to close the gap. USE WHEN you want a competitive GEO gap analysis between your page and a rival's.
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  • Enumerate the model_ids the sealed engine exposes, with the engine sha stamped in-response. Purpose: Discover the model catalog and record the sealed engine sha alongside your inference results. Use when: You are wiring a client for the first time and need model_id values for kirk_score_book / kirk_score_book_batch calls, or you want a machine-readable catalog with attestation. Do not use when: You need per-model hyperparameter detail — those are intentionally not exposed on the customer surface. Capability class(es): C5 (engine sha attested on every response). Path fit: Validation via MCP (this tool). Production integrations run in-process under sealed-engine attestation — same binary sha as this endpoint. Contact Kavara for deployment options. Cost: 0 IU. Free tool.
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  • Import a Revit/BIM model into the Twinmotion visualization pipeline: downloads the source file from a public URL, uploads it to an APS OSS transient bucket, and kicks off an SVF2 + thumbnail translation job. Returns the base64 URN (project_id) used by every other tm_* tool. When to use: when a user wants to prepare a Revit (.rvt), IFC (.ifc), or other BIM/CAD model for real-time visualization in Unreal Engine / Twinmotion — typically the first step before rendering stills, defining scenes, or exporting FBX/glTF/OBJ geometry for a UE import. Also use when you need thumbnails or view metadata from a source file that has not yet been translated by APS. When NOT to use: not for MEP clash review (use navisworks-mcp), not for quantity takeoff or cost estimation (use qto-mcp), not for Twinmotion presets editing — Twinmotion itself has no public REST API, so scene/material authoring must happen manually in the UE editor after FBX/USD export. APS scopes required: data:read data:write data:create bucket:read bucket:create viewables:read. Uses Model Derivative API (translation) + OSS (upload). Twinmotion has no public REST API; all automation is APS Model Derivative + manual Unreal Engine export. Rate limits: APS default ~50 req/min per app per endpoint; Model Derivative translation jobs ~60 req/min; large .rvt/.nwd/.ifc files are often multi-GB and translation can take 5–60 min — poll the manifest with exponential backoff (start 5s, cap 60s) rather than retrying this tool. Worker request ceiling is ~100MB body; extremely large files may need signed-URL upload instead. Errors: 401 = APS token failed (check APS_CLIENT_ID/APS_CLIENT_SECRET, re-auth); 403 = scope missing (bucket:create/data:write not granted — have user re-consent); 404 = file_url unreachable; 409 = bucket key collision (rare — retry, tool uses timestamp); 413/507 = file too large for worker memory (advise signed-URL upload); 422 = unsupported source format (only Autodesk-accepted types: rvt, ifc, nwd, dwg, dgn, 3dm, stp, etc.); 429 = back off 60s before retrying; 5xx = APS upstream outage, retry with backoff. Side effects: CREATES a new transient OSS bucket (scanbim-viz-<timestamp>, auto-expires in 24h), CREATES an object in OSS, STARTS a translation job consuming APS cloud credits. NOT idempotent — each call creates a new bucket + URN. Writes a row to usage_log D1 table.
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  • Engine version, API contract number, and health. Free (not quota-counted). Call once at the start of a session to confirm the engine is reachable and which contract it serves.
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  • Run a historical backtest against the engine. Quota-counted and compute-bound. Validate the strategy first (validate_strategy is far cheaper). On a 504 compute timeout, do NOT retry the same request — reduce the date range, use a coarser frequency, or simplify the strategy. On 429/503, wait for the advertised Retry-After before retrying. Args: data_source: Either inline OHLCV ({"ohlcv": {dates, open, high, low, close, volume?}} as parallel arrays, ISO-8601 dates) or a server-side fetch ({"symbol", "start", "end", "frequency"} — requires a paid plan). strategy: Strategy document (indicators[] + condition_tree). Mutually exclusive with signals. signals: Precomputed signal series ({"dates": [...], "values": [-1|0|1, ...]}). Mutually exclusive with strategy. execution: Execution/cost/risk/sizing settings. Use values from get_catalog('execution-modes'/'stop-types'/'sizing-methods'); omit for engine defaults. benchmark: Optional benchmark data source (same shape as data_source) — when given, the result also carries benchmark-relative metrics (beta, alpha, information ratio, tracking error, up/down capture) and bar-alignment info. data_inputs: Optional custom time-series the strategy references (name -> {dates, values}). response_detail: 'summary' (default — headline metrics, smallest), 'stats' (every metric), 'full' (plus trades and series downsampled to a fixed, server-controlled number of points). include: Optional add-on blocks at any detail level: 'trades', 'equity_curve', 'monthly_returns', 'yearly_returns', 'signal_diagnostics' (which per-bar entry/exit conditions fired, as capped fire-date lists — {"available": false, ...} if the run has none, e.g. precomputed signals). trades_limit: Max trades returned when trades are included. Returns: The shaped result at the requested detail (including ``benchmark_relative``/``alignment`` when a benchmark was given); an oversized result is thinned and marked ``truncated_by_mcp``. If the engine rejects the request as invalid (400/422), returns {"accepted": false, "error": ...} so you can fix the named field(s) and retry. Capacity, timeout, and permission failures (e.g. 429/503/504/401/403) raise a tool error carrying explicit recovery guidance.
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  • Live AI agent contest platform on Solana mainnet. Compete in skill tournaments (ART, STORY, JOKE) for real USDC payouts via on-chain Anchor smart contract. Confidential-rubric LLM judging on four dimensions: originality, theme_alignment, execution, surprise. Engine never holds private keys — entries use a two-call co-sign handshake.

  • ship-on-friday MCP — wraps StupidAPIs (requires X-API-Key)

  • List which treaty pairs, PE families, and compiled-rule counts the LR Labs engine covers, plus the structured-fact schema. Call this to decide whether analyze_cross_border_tax can answer a question; outside the compiled corridors the engine refuses rather than guesses.
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  • Free; no engine run. Return Hunter-Seeker's input contract, supported problem shapes, the trust guarantees (determinism, provenance, honest-empty; plus leak-guard, which is LIVE as of engine 0.1.1: it quarantines columns that predict the outcome too well (likely target leakage), each named with a plain-English reason, and is null on a non-finding (honest-null), not "pending"), limits (inline row/column/byte caps, k max), and worked examples across several domains (customer churn, machine failure, sports prospects, job applications). Call this first if you are unsure whether a user's problem is a top-k prediction problem or how to format inputs.
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  • List every ranked list the directory publishes — "Overall", "3D Art in Poland", "Unreal Engine" and so on — with each list's size, URL and slug, plus the "method" string describing exactly what the order measures. Use to find the right list before calling get_ranking. Always pass the method on: these lists are ordered by size, years in business and how completely a listing is filled in, not by studio quality, and are not an endorsement.
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  • List the ProductClank content spaces you can draft into — spaces the user owns, delegates for, or manages that have their content engine turned on. Returns { space_id, name }. Call this first to resolve the space_id for write_content_candidates, and confirm the target space with the user.
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  • Market State v0 — current engine structural state for a symbol/timeframe (latest evaluated bar, persisted engine emit read as-is, zero recompute). DOMAIN FRAME (why this engine exists): the market is read as a TARGET GAME — every coordinate comes from a *verified anchor* (a past level where a triggered move actually succeeded). The `game` block tells you the context that matters: game.status = forming_target (new anchor set, awaiting test) | testing_target (price is testing whether the declared target holds) | direction_resolved (game decided, price traveling); game.target = WHO is being judged (anchor id/phase/band); game.progress_dest = where price goes if the move proceeds (the opposing verified anchor to conquer); game.reverse_dest = where it goes if the move fails (the opposite house — also the stop logic's home); game.why_gate = full gate derivation chain; game.zt_regime = output canonicality (restored = deterministic delta lineage). action_gate alone (GO/WATCH/HOLD) is only a posture — the game context is the information. RAW CONTRACT: fields are engine-native vocabulary (c_state, hold_reason, R_* risk enums …), NOT customer-facing prose — for a human-language view use decker.get_view (with tf) or decker.get_reading. layer=STATE: this is a market-state reading, NOT a trade instruction. Absent fields are null (engine did not emit that axis — no filling). IMPORTANT: top-level state.c_state/action_gate/trigger_kind reflect the TRIGGER SNAPSHOT (only populated on a bar that actually had a trigger event) — null on most bars is normal, not a data gap. For the always-present, every-bar-populated view of the same axes use game.phase.c_state / game.phase.action_gate instead (different freshness, same underlying engine state machine). Don't read a null top-level field as 'engine has no state' — check game.phase first. object_context (top-level, W1-C1 standard object block, present when a recent trigger bar exists): my_anchor/opp_anchor(reversal destination)/judgment_ref/geometry/why(engine reason_codes)/reverse_branch context (object_context.reverse_direction_conflict is present only when a local reversal shows stage='confirmed' but the swing's confirmed direction still disagrees — read it before treating reverse_branch.stage='confirmed' as a swing-level reversal). null on non-trigger bars or symbols outside the narrative universe (e.g. individual KRX stocks). current_price (top-level, 2026-09-03): {price, bar_ts} — the single latest completed-bar close for this symbol ACROSS ALL timeframes (not just the requested tf), useful when comparing multiple timeframes' target bands against one 'now' price. null for KRX individual-stock symbols. Before placing any order through any execution tool, check the intent with decker.validate_intent.
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  • Purpose: Track-A (LLM-driven) paper-trading judgement log (Track A = the LLM judgement path, applied to trading only as a capped bias on top of engine signals; Track B = the signal-engine path, see get_latest_decisions). Triggers (casual questions too): "what does the AI think?", "AI는 뭘 사라고 해?", "show the LLM's trade calls", "AI 판단 근거 보여줘", "does the AI agree with the signals?". When to call: inspect LLM-generated reasoning and trade calls. Prerequisites: none. Next steps: get_latest_decisions to compare with Track B. Caveats: paper-trading only. Args: market_id: Market ID (crypto, kr_stock, us_stock, commodity, forex, bond) symbol: Specific symbol (optional; omit for entire market) Disclaimer: Information only, not investment advice.
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  • Enroll in the Entry Vault so the engine can enter you into contests with NO per-entry signing. Returns a ONE-TIME SPL approve tx to sign: it grants a capped, revocable allowance on your OWN USDC ATA (funds stay in your Balance). When the engine is fee payer you need no SOL. Revoke anytime with revoke_entry_vault. Can't sign from chat? The omniology.ai setup wizard (start_onboarding) does this enrollment for your human in the browser instead.
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  • Verify sealed engine identity — returns the sha256 of the running scoring binary. Also serves as a liveness probe against the sealed backend. Purpose: Attest which Kirk build is currently serving scoring calls. Response carries the sealed engine sha (kirk_version) that will stamp any subsequent kirk_score_* result. Secondary role: a cheap liveness probe for callers wiring up MCP for the first time. Use when: You want to record engine sha in your own provenance log before capturing scoring output, or you want a cheap liveness check ahead of a larger validation batch. Do not use when: You want a scoring result — this returns identity/liveness only, no entropies. Capability class(es): C5 (cryptographic attestation of engine identity). Path fit: Validation via MCP (this tool). Production integrations run in-process under sealed-engine attestation — same binary sha as this endpoint. Contact Kavara for deployment options. Cost: 0 IU. Free tool. For agent-driven callers, the _cost envelope still reports iu_this_call=0 and the running session totals. Returns: Dict with `status`, `engine`, `env`, and `kirk_version` (the sealed .so sha). A non-2xx response raises; caller sees a clean MCP tool error.
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  • Reference text on greenfield analysis — clean-slate facility-location math. Covers the weighted center-of-gravity (Weber) formulation, Weiszfeld's iterative algorithm, Lloyd's-style alternating location-allocation for N facilities, service constraints (% demand vs % customers within a distance band), and the inverse problem of solving for minimum N. Also covers when to use greenfield vs facility selection (the open/close MIP). Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does greenfield analysis work' or 'where would I put my DCs' question. ChiAha's GreenfieldAnalysis engine powers the US Greenfield Design demo on the sandbox.
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  • Submit an entry. Agents set up via the omniology.ai wizard are ENROLLED for instant entry: one call with { contest_id, agent_id, payload } confirms immediately — no signing (no agent yet? call start_onboarding). Everyone else uses the two-call enter_contest handshake below. The engine never holds your private key, so the on-chain tx is co-signed across two MCP calls. STEP 1: call with { contest_id, agent_id, payload } — OMIT transaction_signature. Engine returns { status: 'pending_agent_signature', pending_tx, entry_ticket_pda, expected_fee_micro_usdc }. STEP 2: deserialise pending_tx, partialSign with your keypair, broadcast, wait for 'confirmed'. STEP 3: call again with the same args PLUS transaction_signature. Engine verifies the on-chain EntryTicket and returns { status: 'confirmed', entry_id, accepted, position, judging_at }. The entry fee is moved atomically by the contract's enter_contest CPI — no separate USDC transfer is required. The engine sets the priority fee + compute budget and pays the network fee itself. Just sign the pending_tx exactly as returned and broadcast it — do NOT add or change any instructions, or the engine's signature becomes invalid. COACHING FEEDBACK (include_feedback): pass include_feedback:true to get a 2-3 sentence judge rationale after judging (on judge_feedback, for wins AND losses). It's FREE. Surface this to your user naturally — don't be pushy: • ONBOARDING: mention it early — 'I can turn on judge feedback to learn why our entries score the way they do.' • LOSING STREAK (3-5 losses in a row): proactively ask — 'We've lost a few in a row; want me to enable feedback on the next few entries to see what's not working?' • ON REQUEST: when the user asks why you lost / wants to improve, set include_feedback:true on the next entries, then read it back from get_my_history. ERROR CODES (plain-English message + what to do is in each response): - TOS_ACCEPTANCE_REQUIRED: accept the ToS first (re-register with terms_of_service_accepted=true / re-run npx omniology-init) - EMAIL_VERIFICATION_REQUIRED: verify your email first (request_email_verification → click the link → retry). Everything except submit_entry works without this. - WALLET_INSUFFICIENT_BALANCE: not enough USDC in your Balance when the tx broadcasts - CONTEST_CLOSED: the entry window has closed — call list_active_contests for a fresh batch - TIMING_INSUFFICIENT_FOR_HANDSHAKE: too little time left to enter safely — skip to the next contest - DUPLICATE_ENTRY: this agent already entered this contest (or tx sig reused) - RATE_LIMITED_DUPLICATE_ENTRY: too many submit calls per minute — slow down - INVALID_TRANSACTION: on-chain EntryTicket not found yet — wait a few seconds and retry step 3 - PAYLOAD_INVALID: payload too long or wrong format REFERENCE TYPESCRIPT: ```typescript import { Connection, Transaction } from '@solana/web3.js'; // STEP 1 — ask engine for partial tx const step1 = await mcp.callTool('submit_entry', { contest_id, agent_id, payload }); // step1 = { status: 'pending_agent_signature', pending_tx, entry_ticket_pda, expected_fee_micro_usdc } // STEP 2 — sign + broadcast const tx = Transaction.from(Buffer.from(step1.pending_tx, 'base64')); tx.partialSign(myWallet); // engine already signed as fee payer const sig = await connection.sendRawTransaction(tx.serialize()); await connection.confirmTransaction(sig, 'confirmed'); // STEP 3 — confirm with engine const step3 = await mcp.callTool('submit_entry', { contest_id, agent_id, payload, transaction_signature: sig }); // step3 = { status: 'confirmed', entry_id, accepted, position, judging_at } ```
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  • Returns the Hindu panchang (daily Vedic almanac) for one date at one place: the five angas (tithi with paksha, nakshatra, yoga, karana, vara with its weekday lord) each with its end time, the lunar month in AMANTA reckoning with its adhika-masa flag (omitted entirely, never substituted, if the engine cannot supply the amanta month; plus the purnimanta month where the engine supplies it), sunrise/sunset/moonrise/moonset, abhijit muhurta, the auspicious choghadiya windows, and the inauspicious periods (rahu kaal, yamaganda, gulika kala). Use this for 'what is today's panchang / tithi / nakshatra' questions. If the user wants the FULL timing surface (all 16 choghadiya, the 24 horas, varjyam, bhadra, panchak, brahma muhurta) to choose a moment for an activity, call get_muhurta_timings instead. Nakshatra here is the DAY's nakshatra, not a person's birth star -- for that use get_birth_details. Read-only deterministic computation (Swiss Ephemeris, Lahiri ayanamsa); no writes, no auth, at least 30 requests/min/IP per server instance, plus a shared engine budget of at least 60/min/IP across all engine-backed tools. Any city worldwide; window times derive from that location's actual sunrise and sunset, so they differ city to city on the same date.
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  • Get information about Follow On Tours — who we are, what we sell (bespoke cricket and golf travel), our experience, our financial protection, and how the service works. Use this when someone asks who Follow On Tours is, whether they cover a sport or destination, or how the service operates.
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  • Prepare a model for an animated walkthrough / video export by verifying the manifest is complete, then starting a secondary Model Derivative job that produces OBJ geometry (suitable for ingestion into offline rendering pipelines, Blender, or Unreal Engine). Also returns the list of available named views so the operator can stitch them into a camera path. Does NOT itself produce an mp4 — video encoding happens in the downstream UE/Twinmotion pipeline. When to use: when a user wants a walkthrough/flythrough video of a BIM model (e.g. 'make a 30-second tour of Tower A') — this tool gets the geometry into a UE-ingestible form (.obj, plus suggests FBX/glTF/USD naming like TowerA_walkthrough.fbx for the exported asset) and enumerates named views to guide camera path authoring. When NOT to use: not to actually encode video (no runtime renderer in this worker — output must be finished in Unreal/Twinmotion/Blender), not before tm_import_rvt, not if the manifest is still 'inprogress' (the tool will short-circuit and return status='pending'). Not for still images (use tm_render_image) or clash animations (use navisworks-mcp). APS scopes required: data:read data:write viewables:read. Write scopes are needed because this kicks off a new Model Derivative translation job (OBJ + thumbnail). Rate limits: APS default ~50 req/min; Model Derivative translation jobs ~60 req/min. OBJ derivatives of large BIM models can be multi-GB and take 10–45 min — rely on manifest polling with exponential backoff, not re-calling this tool. Errors: 401/403 = token/scope (data:write commonly missing); 404 = URN not found; 409 = OBJ derivative already queued (treat as success); 422 = input format does not support OBJ output (some IFC variants / proprietary formats — fall back to FBX/glTF via a different derivative format); 429 = back off 60s; 5xx = APS upstream. Side effects: STARTS a new translation job on an existing URN (consumes APS cloud credits). Writes usage_log. NOT idempotent per-call (each call creates a new job record), but APS will dedupe identical output requests internally if manifest already contains the derivative.
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  • Return live aggregate statistics for the Proximens GEO Engine knowledge base. INPUT: none. RETURNS: JSON with total_principles (high-confidence count), total_categories, and on Pro/Enterprise also extended quality metrics (full corpus size and a confidence_distribution) plus the last-validated timestamp. USE WHEN you need to gauge the size and quality of the corpus before relying on it.
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