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Glama

Country State City

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.

TDQS

A4.3/5.0
Behavior5/5

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

The description provides extensive behavioral details beyond the annotations (readOnlyHint=true, etc.). It explains market resolution, classification, fan-out, response shapes, resolver contract with confidence levels, parent event extraction, news fallback behaviors, safety short-circuits for low confidence or closed markets, wide-spread illiquidity handling, and cancellation rules. No contradictions with annotations.

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 front-loaded with the core purpose and usage. It efficiently packs many behavioral details into clearly separated sections (RESPONSE SHAPES, RESOLVER CONTRACT, etc.). Every sentence adds value, though some details (e.g., candle-stick futures from 2026) could be streamlined. Overall, it is well-structured for the complexity.

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

Completeness4/5

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

Given the tool's complexity and lack of output schema, the description covers the return structure comprehensively (market, analysis, evidence, match confidence, parent events, news fields). It also documents error/edge cases (low confidence, closed markets, wide spreads). A minor gap is not enumerating all possible data sources, but the fan-out examples suffice.

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%, so the baseline is 3. The description does not add significant meaning beyond the schema; it mostly reiterates the parameter purposes from the schema. While the description provides examples of usage, it does not clarify parameter constraints or edge cases beyond what the schema already captures.

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 clearly states the tool researches a Polymarket bet by pulling Pipeworx data in one call. It specifies the inputs (market slug, URL, or question text) and explicitly lists use cases: 'should I bet on X', 'what does the data say about Y', 'is there edge in Z'. This distinguishes it from sibling tools like polymarket_edges or polymarket_arbitrage, which serve narrower purposes.

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 provides explicit use cases for when to use this tool ('Use for...'), giving clear context. However, it does not explicitly mention when not to use it or name alternatives among sibling tools, which would strengthen guidance. The examples effectively imply the tool is for comprehensive research, not quick checks or arbitrage.

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

A3.7/5.0
Disambiguation2/5

Several tools overlap enough to cause misselection: ask_pipeworx and ask_pipeworx_beta are functionally identical right now, ask_pipeworx_grounded and validate_claim both handle factual lookup/verification, and ai_visibility_check/scan_competitor_ai_presence are near duplicates in scope. The country/state/city tools are distinct but sit in a pile of unrelated Pipeworx tools, adding confusion.

Naming Consistency3/5

All names are lower_snake_case and families like polymarket_* and ask_pipeworx* help group tools, but the verb_noun convention is inconsistent: entity_profile, deep_research, recent_alerts, and pipeworx_trending are noun phrases, while remember/forget/subscribe are bare verbs. It is readable but not a predictable pattern.

Tool Count2/5

34 tools is above the practical ceiling for a focused MCP server, and the mismatch is severe: only 3 tools match the 'Country State City' name while 31 belong to a broad Pipeworx platform. A geographic server would need roughly 3-6 focused tools; this surface is bloted.

Completeness2/5

For the stated Country State City domain, list_countries/get_states/get_cities provide the basic hierarchy, but there is no city search, country/state detail lookup, or attribute discovery beyond the three list endpoints, making the useful geographic surface thin. For the Pipeworx domain the coverage is broader, but that confirms the identity mismatch and obscures the server's actual purpose.

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