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Glama

Usgs Earthquakes

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. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint/openWorldHint/idempotentHint, and the description goes far beyond by adding critical behavioral context: resolver contract (market_match_confidence, alternatives, suggestions), parent_event extractor for partitioned bets, news fallback mechanics (_fallback_attempted, retry_after_sec), safety short-circuit status, closed-market status, wide-spread tradeability, and resolution-rule risk. This is exceptionally transparent and directly actionable.

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 well-structured with CAPITALIZED section headers (CLASSIFIERS, FAN-OUT EXAMPLES, RESPONSE SHAPES, RESOLVER CONTRACT, PARENT_EVENT EXTRACTOR, NEWS FIELDS, SAFETY, RESOLUTION-RULE RISK) and front-loaded core purpose. Every section earns its place for a complex tool with no output schema, though some fan-out examples and repetition could be trimmed. It's appropriately sized for the tool's complexity but not maximally concise.

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 carries full responsibility for explaining return shapes and edge behavior. It covers response fields (market, analysis, evidence), resolver contract, parent-event partition, fallback handling for news, safety short-circuit, closed/inactive markets, illiquid-wide-spread, and cancellation-rule risk. This is unusually complete for a complex tool with 3 parameters and no output schema.

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 schema already describes market slug/URL/question text, depth enum, and include_raw. The description reinforces the market parameter with examples but doesn't add significantly new parameter-level detail beyond the schema. It does, however, contextualize how the market value influences fan-out and response shape, which keeps it at baseline rather than above.

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 and resource: 'Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call.' It clearly distinguishes the tool from siblings by focusing on single-bet research with fan-out, while siblings like polymarket_edges or polymarket_arbitrage target different analyses. The scope is explicit: it resolves the market, classifies the bet, fans out, and returns an evidence packet.

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 when to use the tool: 'Use for "should I bet on X", "what does the data say about Y", or "is there edge in Z".' It also gives detailed fan-out examples and safety behavior (low-confidence short-circuit, closed-market handling), which helps agents understand what they'll get. However, it doesn't explicitly say 'when not to use' or name alternative tools for exclusion, so it stops short of a 5.

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

A3.6/5.0
Disambiguation1/5

The tool set is dominated by tools unrelated to USGS earthquakes (e.g., Polymarket betting, company profiles, memory operations). An agent would find it nearly impossible to distinguish the few earthquake-specific tools from the multitude of unrelated ones, leading to severe misselection.

Naming Consistency3/5

Most tool names follow a verb_noun pattern with underscores (e.g., search_earthquakes, count_earthquakes), which is consistent. However, the variety of verbs and domains creates a sense of incoherence, and some tool names are overly generic (e.g., process, run) in the broader context, though those are not present here. The naming pattern is acceptable but the inconsistency in domain scope reduces clarity.

Tool Count1/5

With 29 tools but only 3 directly related to earthquakes, the tool count is grossly inappropriate. The server's name suggests a focused purpose, but the vast majority of tools belong to other domains (e.g., Pipeworx queries, Polymarket betting, company data). This extreme mismatch makes the tool set bloated and misleading.

Completeness2/5

For earthquake data, the server provides only search, count, and get by ID. Missing are common operations like listing recent quakes, subscribing to alerts, or updating/correcting data. The coverage is minimal and insufficient for a comprehensive earthquake tool server, leaving significant gaps that agents could not work around.

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