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Glama

microlink

by io.github.pipeworx-io

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. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "market_input": "will fed cut rates in june 2026"
+  },
+  {
+    "market_input": "https://polymarket.com/event/will-bitcoin-hit-150k-by-june-30-2026"
+  }
+]
  3. Changed1 schema field changed
    • addedInput schema / properties / include_raw
      Added value: +{
+  "description": "Default 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.",
+  "type": "boolean"
+}
  4. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description goes far beyond them by disclosing fan-out behavior, resolver confidence levels, blocking statuses (low_confidence_match, market_closed_or_inactive), liquidity warnings, cancellation-rule risk, and news fallback mechanics. This is exceptionally rich behavioral context.

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?

The description is long but highly structured with all-caps section headers (CLASSIFIERS, FAN-OUT EXAMPLES, RESPONSE SHAPES, RESOLVER CONTRACT, SAFETY) that make it scannable. Every paragraph carries a distinct, useful behavioral fact; it's dense rather than padded, though a slightly shorter version could exist without losing critical information.

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?

With no output schema, the description fully specifies the response envelope: market fields, analysis fields, evidence keys, parent_event structure, news fields, statuses, and cancellation-rule semantics. It covers blocking routes, edge cases, and when to distrust the analysis, making the tool nearly self-documenting.

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 coverage is 100% and each parameter already has a clear description and examples. The tool description reinforces the accept-any-input-format behavior but doesn't add new parameter-level semantics beyond what the schema provides; the value it adds is about fan-out behavior and response shapes, not parameter details.

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?

The description opens with a specific verb+resource ('Research a Polymarket bet by pulling the relevant Pipeworx data') and clearly differentiates itself from siblings like polymarket_edges and validate_claim by positioning itself as a one-call data-pull research tool. It also names concrete user intents ('should I bet on X', 'is there edge in Z'), making its purpose unmistakable.

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?

The description explicitly states 'Use for' with three query phrasings, giving clear context for when to invoke the tool. It does not explicitly name alternative tools to avoid, but the use-case framing effectively distinguishes it from trade/arbitrage-focused sibling tools.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed usage guidance, but the several query entry points (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) overlap conceptually and require careful reading to select correctly. Notably, ask_pipeworx_beta currently behaves identically to ask_pipeworx, which could cause confusion.

Naming Consistency3/5

Tool names mix verb-first (remember, resolve_entity) and noun-first (entity_profile, deep_research) patterns, with some using prefixes like 'polymarket_' or 'ask_pipeworx'. While all are snake_case and readable, the lack of a single consistent convention makes the set feel less coherent than it could be.

Tool Count3/5

33 tools is on the high end for a single server, though the broad domain (data retrieval, prediction markets, memory, subscriptions, web scraping) justifies much of the sprawl. Still, the count borders on heavy, and some tools could potentially be consolidated (e.g., the ask_pipeworx variants).

Completeness4/5

The toolset provides comprehensive coverage for its core data querying and analysis domain, with lifecycle coverage for memory and subscriptions. Minor gaps exist, such as no generic 'fetch page content' tool despite having get_metadata and take_screenshot, but these do not undermine the primary functionality.

Resources