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Conceptnet

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint) indicate safe, read-only, open-world behavior. The description adds critical behavioral details: the 'FILL CHECK' explains that realizable_edge_pp ≤ 0 means the arbitrage is not tradeable, and it references polymarket_fill_risk for custom sizing. No contradiction 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 comprehensive but slightly verbose. It is well-structured with clear sections (modes, semantic anchor, partition filter, response details, fill check). Every sentence adds value, though some details 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?

Despite no output schema, the description thoroughly explains the response structure (opportunities array with fields, partition_check object, fill check details). It also addresses edge cases (low similarity, placeholder filter) and references a sibling tool for custom sizing, making it complete for agent use.

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?

Input schema has 100% coverage with descriptions for both parameters (event, topic). The description enriches these by explaining that event takes a slug (with examples) and topic takes a seed question, and it details how these modes affect the analysis (walking child markets, cross-event scanning, similarity checks).

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 + partition-sum checks.' It distinguishes itself from sibling tools like polymarket_edges by focusing on arbitrage detection through specific mathematical checks, and it details three distinct usage modes (no args, event, topic) with specific behaviors.

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?

Provides explicit guidance: 'Call with NO args for a trending_scan... pass event for the strongest per-event partition_check, or topic for a themed cross-event scan.' Recommends event mode for specific markets and explains when cross-event mode is beneficial. No explicit when-not-to-use, but the clarity of modes makes it highly usable.

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

A3.5/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical, and the five polymarket_* tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) all target prediction-market opportunities. The memory tools (remember/recall/forget) are distinct, as are subscriptions, but the routing and Polymarket clusters create real misselection risk.

Naming Consistency3/5

All names are snake_case, but the pattern is mixed: some are verb_noun (ask_pipeworx, compare_entities, discover_tools, resolve_entity), some are noun_verb or adjective_noun (bet_research, entity_profile, pipeworx_trending, recent_changes), and some are bare nouns/verbs (lookup, query, recall, relatedness). The 'polymarket_*' and 'ask_pipeworx*' families are consistent internally, but the overall set lacks a uniform verb-first convention.

Tool Count2/5

With 34 tools, the server is heavily over-scoped for a server named 'Conceptnet' — the vast majority of tools belong to a separate Pipeworx data-access product, not a semantic-network API. While each tool has a use, the count feels bloated and the server name misrepresents the actual surface.

Completeness4/5

The ConceptNet portion is complete (lookup, query, relatedness cover graph traversal). The Pipeworx portion is also fairly complete: universal router, grounded mode, deep research, entity profiles, comparisons, claim validation, subscription lifecycle, memory, and feedback. Minor gaps exist (e.g., no direct SEC filing fetch without going through ask_pipeworx), but the meta-tools mostly fill them.

Resources