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Insee

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

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idlempotentHint=true, destructiveHint=false. The description vastly expands with detailed behavioral traits: resolver contract (market_match_confidence, alternatives, suggestions), parent_event extractor, news fields with fallback logic, safety short-circuits (low_confidence_match, market_closed_or_inactive), wide-spread warnings, and resolution-rule risk parsing. This comprehensive disclosure far exceeds the annotation baseline.

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?

The description is very long (multiple paragraphs) and could be more concise. However, it is front-loaded with the core purpose and uses section headers (RESPONSE SHAPES, RESOLVER CONTRACT, etc.) for structure. Some details are repeated (e.g., low_confidence_match explained twice). While informative, it could be trimmed without losing clarity.

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?

Given the complexity (classifiers, fan-out, response shapes, safety mechanisms, and edge cases), the description is remarkably complete. It covers input variants, output structure, error states (low confidence, closed markets, wide spreads), and even resolution-rule risk. Without an output schema, the verbal descriptions of response shapes are sufficiently detailed for an agent to understand what to expect.

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% for all three parameters. The description adds significant value beyond the schema: it clarifies the 'market' parameter accepts slugs, URLs, or question text; explains the 'depth' enum (quick vs thorough) with default; and elaborates on 'include_raw' with purpose and size trade-offs. This goes beyond the schema's basic descriptions.

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 immediately states the verb 'Research' and the resource 'a Polymarket bet'. It distinguishes this tool from siblings like polymarket_arbitrage and polymarket_edges by detailing its unique capability: pulling Pipeworx data in one call with market resolution, classification, and fan-out across categories.

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 lists use cases: 'should I bet on X', 'what does the data say about Y', 'is there edge in Z'. It provides concrete examples across multiple categories (BTC, Fed, Hormuz, etc.). While it does not explicitly state when not to use, the sibling tools provide alternatives, and the usage context is clear.

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

A3.9/5.0
Disambiguation3/5

Most tools have detailed, carve-out descriptions, but ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share the same routing core, with the beta version currently identical to the stable one. The Polymarket and company-research clusters are better differentiated, but the number of overlapping research/query entry points still creates real selection risk.

Naming Consistency3/5

The set is consistently snake_case and has coherent prefixes like ask_pipeworx_ and polymarket_, but it mixes verb_noun names (resolve_entity, scan_dependency, discover_tools) with noun-phrase names (entity_profile, bet_research, recent_changes) and one-word verbs (remember, recall, forget). The naming is readable but does not follow one predictable pattern.

Tool Count2/5

With 32 tools, the server exceeds the 25+ threshold for too many tools and feels like a broad platform dump rather than a focused toolkit. Several utility, memory, and meta-discovery tools could reasonably live in separate servers, and the Insee name makes the breadth especially unfocused.

Completeness4/5

For the broad data-research platform it actually exposes, the coverage is strong: general lookup, grounded verification, deep research, entity resolution, company profiles, comparisons, change feeds, subscriptions, and memory all have working lifecycles. The main gap is that some unrelated utilities like scan_dependency and generate_llms_txt feel tacked on rather than part of a missing core workflow.

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