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Worldbank Poverty

by io.github.pipeworx-io

Polymarket Arbitrage

polymarket_arbitrage
Read-onlyIdempotent

Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a trending_scan of the top ~200 markets by weekly volume; pass event for the strongest per-event partition_check, or topic for a themed cross-event scan. event (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). topic (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventNoSingle-event mode (use this if you know the specific Polymarket event): event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k". Full Polymarket URLs also accepted.
topicNoCross-event mode (use this if you want to scan related events across the platform): a topic or seed question like "Fed rate decision" or "Strait of Hormuz traffic returns to normal". Tool searches Polymarket for related events and checks monotonicity across them.

TDQS

A5/5.0
Behavior5/5

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

Annotations indicate readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false. The description adds significant behavioral context: scanning process, partition filter, semantic anchor for cross-event similarity, fill check against live CLOB depth. 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.

Conciseness5/5

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

The description is comprehensive yet well-structured with sections (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK). Every sentence adds value, no fluff. It balances detail with readability.

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?

Despite no output schema, the description thoroughly explains the response structure (opportunities[], partition_check, fill check) and references a sibling tool for custom sizing. Given the tool's complexity (optional parameters, multiple modes), the description covers all necessary context.

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

Parameters5/5

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

Schema coverage is 100% with descriptions for event and topic. The description adds meaning beyond the schema: example slugs, acceptable URLs, explanation of what each mode does internally, and the recommended usage for event mode. Rich parameter semantics.

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's purpose: find arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It distinguishes three modes (no-args trending scan, event-specific, topic-based cross-event) and explains the underlying algorithms. No ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use each mode: no args for trending scan, event for a specific market (recommended), topic for cross-event scanning. It also warns against trading when realizable_edge_pp <= 0 and directs to polymarket_fill_risk for custom sizing. Provides clear when-to-use and when-not-to-use guidance.

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
Disambiguation2/5

Many tools have overlapping purposes, especially the pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) which all route to the same data sources. Additionally, the server includes unrelated meta-tools (remember/recall/forget, generate_llms_txt, pipeworx_feedback) that have no clear boundaries with the poverty data tools, and betting tools that seem out of place. The core poverty tools (get_poverty, get_poverty_regional, list_reference) are distinct, but the rest creates significant confusion.

Naming Consistency2/5

Tool names are a mix of styles: some use snake_case (get_poverty, list_reference, suggest_questions), some use camelCase (ask_pipeworx, bet_research, scan_competitor_ai_presence), and others are single words (recall, remember, forget, subscribe). The naming pattern is highly inconsistent, making it hard to predict related tool names.

Tool Count2/5

With 34 tools, this server is heavily overloaded for a 'Worldbank Poverty' server. The majority of tools are unrelated to poverty (Polymarket betting, AI marketing, npm package checks, LLM visibility). The core poverty functionality could be served by 3-5 tools, but instead the server includes dozens of extra tools from a generic data platform, making the count inappropriate for the stated domain.

Completeness4/5

For the poverty data domain, the tool surface is actually quite complete: get_poverty for country-level data, get_poverty_regional for aggregations, and list_reference for metadata. The only minor gap is a lack of a tool for comparing poverty across countries directly, but that is easy to work around by calling get_poverty multiple times. The extra meta-tools do not affect poverty data completeness.

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