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Glama

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-bitcoin-hit-150k-by-june-30-2026"), a polymarket.com URL, or a question text. 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. In practice resolved markets are usually de-indexed and instead surface via the low_confidence_match path above — 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

TableJSON Schema
NameRequiredDescriptionDefault
depthNoquick = 2-3 evidence sources, thorough = full fan-out. Default thorough.
marketYesPolymarket slug ("will-bitcoin-hit-150k-by-june-30-2026"), full URL ("https://polymarket.com/event/..."), or question text ("Will Bitcoin hit $150k by June 30?")
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. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "market_input": "will fed cut rates in june 2026"
      -  },
      -  {
      -    "market_input": "https://polymarket.com/event/will-bitcoin-hit-150k-by-june-30-2026"
      -  }
      -]New value: +[
      +  {
      +    "market": "will-bitcoin-reach-100k-in-july-2026"
      +  },
      +  {
      +    "market": "https://polymarket.com/event/will-bitcoin-hit-150k-by-june-30-2026"
      +  }
      +]
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint. Description adds extensive behavioral details: response shapes, resolver contract, parent event extractor, news fields, safety (low-confidence, closed markets), wide spreads, resolution-rule risk. Adds significant value beyond annotations; no contradiction.

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

Conciseness3/5

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

Description is detailed but verbose (multiple paragraphs). Front-loaded with purpose, then extensive details. Every sentence adds value, but could be more concise. Structured with sections (RESPONSE SHAPES, RESOLVER CONTRACT, etc.)

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?

No output schema, so description must cover return values. It thoroughly explains response shapes, resolver contract, parent event, news fields, safety, etc. Given complexity, it is complete.

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

Parameters4/5

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

Schema coverage is 100%; description adds context like examples, depth explanation, include_raw behavior. Baseline 3, description adds marginal value, so 4.

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?

Description explicitly states the tool researches Polymarket bets by pulling PipeWorx data, resolving markets, classifying, and fanning out. It distinguishes from siblings like polymarket_edges by focusing on single-bet research. Verb+resource: 'Research a Polymarket bet'.

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?

Clearly states when to use: 'should I bet on X', 'what does the data say about Y'. Provides examples of classification and fan-out. Lacks explicit when-not or alternatives, but context is strong.

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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TDQS

A3.5/5.0
Disambiguation2/5

Several clusters of tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all route/discover questions across the same 5,743 tools, differing mainly in mode or betaness. The polymarket_* family (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) similarly overlaps in prediction-market edge detection. An agent would frequently struggle to pick the right tool from these near-duplicate groups despite verbose descriptions.

Naming Consistency3/5

Snake_case is used throughout, but patterns are mixed: some tools are verb-first (ask_pipeworx, find_sites, recall, forget, subscribe), some are noun phrases (current_conditions, entity_profile, bet_research), and some use a domain prefix (pipeworx_*, polymarket_*). The version-suffixed ask_pipeworx_beta is also a minor deviation from the otherwise clear descriptive style.

Tool Count2/5

34 tools is excessive for a server named 'Usgs Water' since only 3 tools (current_conditions, daily_values, find_sites) actually relate to USGS water data. Even as a general Pipeworx platform server, the count is heavy, with many tools dedicated to niche prediction-market trading and meta-routing that inflate the surface.

Completeness1/5

Against the stated USGS Water purpose, the surface is severely incomplete: it lacks water-quality samples, groundwater data, site metadata details, historical statistics, rating curves, parameter code lookup, and flood/alert data. The remaining 31 tools cover an entirely different domain (SEC filings, drugs, prediction markets, npm scans, memory), so agents using this server for water data will hit dead ends almost immediately.