Skip to main content
Glama

Worldbank Projects

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?

The description goes far beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint=false) by explaining the internal logic: monotonicity checks, partition-sum validation, the 3pp deviation threshold, semantic similarity anchor (Jaccard ≥0.30), placeholder filtering, and the fill check that warns against trading if realizable edge ≤ 0. It also discloses return structure. This is 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.

Conciseness5/5

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

Although long, the description is tightly organized with clear section headers (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK) and front-loaded with the core purpose. Every sentence earns its place by explaining a distinct behavior or mode, and there is no redundancy or filler.

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?

The tool has optional parameters, no output schema, and considerable complexity, but the description covers all essential aspects: usage modes, input formats, algorithmic filtering, output fields, and a critical warning about fill checks. It also points to a sibling tool for additional functionality, making it complete for an agent to invoke and understand the result.

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?

Both parameters already have good schema descriptions (100% coverage), but the main description adds substantial value: it explains the difference between event slugs and topics, gives concrete examples ('fed-decision-may-2026', 'Strait of Hormuz traffic returns to normal'), and describes the behavior for each mode. This goes well beyond the schema.

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, multi-part purpose: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It clearly identifies the tool's resource (Polymarket) and mechanism, and the detailed mode breakdown (trending_scan, event, topic) further distinguishes it from sibling tools like polymarket_edges and polymarket_fill_risk.

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?

Usage guidance is explicit and actionable. It states when to call with no args, when to pass `event` (recommended for a specific market), and when to pass `topic` (for cross-event scanning). It also explicitly points to a sibling tool: 'For custom sizing use polymarket_fill_risk.' This meets the highest bar for usage differentiation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Worldbank Projects toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation3/5

Tools are generally distinguishable by name and description, but there are several similar query/verification tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim) and multiple meta-tools (discover_tools, suggest_questions), causing some ambiguity for agents.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use verb_noun (search_projects, validate_claim), others are noun_preposition_noun (projects_by_country), single verbs (remember, forget), or compound phrases (generate_llms_txt). No clear pattern.

Tool Count1/5

33 tools is excessive for a server named 'Worldbank Projects', as only 3-4 tools directly relate to Worldbank data. The rest are generic Pipeworx utilities and unrelated domains, making the tool count inappropriate for the server's stated purpose.

Completeness1/5

For the domain of Worldbank Projects, only basic lookup and search tools are provided (search_projects, get_project, projects_by_country). Missing essential CRUD operations, filtering by sector/theme, or project lifecycle management. The server's tool surface is severely incomplete for its intended focus.

Resources