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Bet Research

bet_research
Read-onlyIdempotent

Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-kristi-noem-win-the-2028-republican-presidential-nomination"), a polymarket.com URL, or a question text. A dated slug ("...-by-june-30-2026") still resolves after it settles — the resolver retries a closed-market lookup rather than giving up on the bare one — so either dated or undated works; prefer whichever slug you actually have. The tool resolves the market, classifies the bet, fans out to category-specific data packs in parallel, and returns an evidence packet + simple market-vs-model comparison. Use for "should I bet on X", "what does the data say about Y", or "is there edge in Z". CLASSIFIERS: crypto_price, fed_rate, geopolitical, sports, sports_championship, drug_approval, election_candidate, tech_launch, space_launch, corporate, corporate_earnings, corporate_event, public_figure_speech, weather, other. FAN-OUT EXAMPLES: BTC bet → coingecko + fred + gdelt+gnews; Fed bet → fred (DFEDTARU + EFFR + CPIAUCSL) + kalshi_macro (KXFED implied probs) + recent_fed_actions (federal-register rules, last 365d); Hormuz bet → imf_portwatch + airspace + gdelt; Yankees WS → mlb_stats_standings + parent_event partition + news; hottest-year bet → climate_projection_nyc + gistemp_latest (NASA global anomaly, rank since 1880) + news; NVDA-vs-AAPL → finnhub get_quote + edgar shares-outstanding (derived market cap) + edgar filings + news. RESPONSE SHAPES: result.market carries best_bid/best_ask/spread_pp/liquidity/price_change_1h/1d/1w; result.analysis carries model_probability/edge_pp/kelly_fraction_half when a closed-form model fires PLUS a 24h-move warning ("Market moved X.Xpp in 24h, comparable to model edge — your edge may already be priced in") when relevant; result.evidence is keyed by source. RESOLVER CONTRACT: result.market_match_confidence ∈ {high, medium, low, none}, market_match_score (0-1 token-overlap), market_match_alternatives[] (other candidate markets the resolver considered), and suggestions[] (explicit re-query hints when the match is fuzzy) — ALWAYS inspect these before trusting the analysis block, because medium/low matches can still surface other fields. PARENT_EVENT EXTRACTOR: when the bet is one leg of a partition (Yankees WS, Romania election), result.parent_event{matched_candidate, top_legs_by_price[], partition_size, placeholders_filtered} gives you the peer prices in one place — that's the headline for elections/championships. NEWS FIELDS: news entries carry _fallback_attempted / _fallback_failed_reason / retry_after_sec when GDELT 429s and GNews backfill ran or failed. SAFETY: low-confidence resolutions short-circuit with status:"low_confidence_match" and suppress analysis fields so agents can't accidentally size on phantom matches. Closed/dead markets that ARE still indexed by Polymarket (yes_price≈0, no volume, no liquidity) return status:"market_closed_or_inactive" and skip fan-out. A market whose own deadline has already passed returns status:"market_expired_or_resolved" + expired_deadline (the date), which is deliberately NOT the same answer as low_confidence_match: your slug was right and is merely settled, so the useful retry is the successor market for the same question, not a corrected spelling. Both routes are BLOCKING, just different mechanisms. Wide-spread markets (>10pp) carry tradeability:"illiquid_wide_spread" + an explanatory note. RESOLUTION-RULE RISK: market.cancellation_rule parses the void/postponement settlement out of the resolution text — refund_50_50 (shares settle flat 50¢ on void; EV-material for any entry away from 50¢, with ev_impact quantified), resolves_no_on_cancel, resolves_yes_on_cancel, carries_to_reschedule, or mentioned_unclear. null means the description never mentions cancellation. Check this before sizing sports/esports/event-occurrence bets — audited arb-bot ledgers show flat-50¢ void settlements are a recurring pure-rules loss.

Input Schema

NameRequiredDescriptionDefault
depthNoquick = 2-3 evidence sources, thorough = full fan-out. Default thorough.
marketYesPolymarket slug ("will-kristi-noem-win-the-2028-republican-presidential-nomination"), full URL ("https://polymarket.com/event/..."), or question text ("Will Bitcoin hit $150k?"). Dated slugs still resolve after they settle — the resolver retries a closed-market lookup — so either a dated or undated slug works.
include_rawNoDefault false. When false (recommended), FRED/FDA/GDELT/Federal-Register evidence is summarized to the few fields agents actually use — keeps responses under ~20KB. Pass true to get full upstream payloads (50KB-500KB) when you need to recompute deltas, cite specific observations, or post-process.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / market / description
      Previous value: -"Polymarket slug (\"will-kristi-noem-win-the-2028-republican-presidential-nomination\"), full URL (\"https://polymarket.com/event/...\"), or question text (\"Will Bitcoin hit $150k?\"). Dated slugs stop resolving once they settle — Polymarket de-indexes resolved markets — so prefer an undated one."New value: +"Polymarket slug (\"will-kristi-noem-win-the-2028-republican-presidential-nomination\"), full URL (\"https://polymarket.com/event/...\"), or question text (\"Will Bitcoin hit $150k?\"). Dated slugs still resolve after they settle — the resolver retries a closed-market lookup — so either a dated or undated slug works."
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only/idempotent/open-world, yet the description adds substantial behavior the annotations cannot: explicit status codes (

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose then organized into labelled blocks (CLASSIFIERS, FAN-OUT EXAMPLES, RESPONSE SHAPES, RESOLVER CONTRACT, SAFETY, RESOLUTION-RULE RISK), and every block carries operational detail an agent would otherwise have to discover by trial. It is long and a few items repeat (the dated-slug retry appears here and again in the schema), which keeps it from a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex, multi-source research tool with no output schema, the description discloses the response shape (market, analysis, evidence keys), the resolver-confidence contract, the parent-event block, news fallback fields, and every short-circuit status. An agent has enough to call it, interpret it, and decide whether to trust the analysis.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the property descriptions already document slug vs URL vs question text, the dated-slug retry behavior, and the depth/include_raw defaults. The description's slug guidance largely restates the schema, and it never mentions depth or include_raw at all. Baseline 3 applies when the schema carries the parameter burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource ('Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call') and immediately names what the call actually does: resolve the market, classify the bet, fan out to data packs, return an evidence packet plus market-vs-model comparison. That is clearly distinguishable from sibling tools like polymarket_edges or resolution_audit, which do narrower jobs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete trigger phrasings ('should I bet on X', 'what does the data say about Y', 'is there edge in Z') and scopes the tool to a single market's research. It never names a sibling or states an explicit exclusion — e.g. when to prefer polymarket_arbitrage or resolution_audit instead — so an agent still has to infer the boundary from the other tools' names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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