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Realestate

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

A4.7/5.0
Behavior5/5

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

Annotations indicate readOnlyHint, idempotentHint, and destructiveHint false. The description adds extensive behavioral context: explains arbitrage detection logic, output structure, fill check, semantic anchor, partition filter, and references to other tools. 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.

Conciseness4/5

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

The description is detailed and well-structured, with front-loaded purpose and clear separation of modes. It is relatively long (about 300 words) but every sentence adds value. Slightly verbose but not overly so.

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 tool has 2 optional parameters and no output schema, the description provides complete context: input modes, output format (opportunities array, partition check, fill check), edge cases (partition filter, low similarity), and references to related tools. No gaps.

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 both parameters described. The description adds significant meaning: explains event slug and full URL acceptance, topic as a seed question, and the behavior of each mode. This goes beyond the schema 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 clearly states the tool's purpose: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It specifies the verb, resource, and method, and distinguishes 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 Guidelines4/5

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

The description provides clear guidance on when to use each mode: no args for trending scan, 'event' for specific market, 'topic' for cross-event scanning. It explains the benefits of cross-event mode and recommends 'event' for specific markets. However, it does not explicitly state when not to use this tool versus other sibling tools.

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

A3.8/5.0
Disambiguation2/5

Multiple tools occupy the same natural-language lookup niche: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions, and the beta tool is currently described as identical to the stable router. Prediction-market edge detection also fans out across bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, and polymarket_fill_risk, so an agent can easily select the wrong one.

Naming Consistency4/5

Most names follow a predictable snake_case action-first pattern (ask_pipeworx, resolve_entity, subscribe, unsubscribe) with helpful domain prefixes for polymarket_*, realestate_*, and pipeworx_*. Minor deviations exist—entity_profile is noun-first, ask_pipeworx lacks an underscore, and remember/forget/recall are bare verbs—but they do not create real confusion.

Tool Count2/5

33 tools is well above the coherence sweet spot and the rubric's 25+ threshold. The count is inflated by auxiliary platform utilities (feedback, trending, memory, subscriptions, llms.txt generation, npm scanning) that are unrelated to the Realestate name and make the tool surface feel like a full platform rather than a focused MCP server.

Completeness2/5

For a server named Realestate, the surface is only minimally complete: realestate_municipalities and realestate_transactions cover Japanese transaction lookups, but there are no tools for property listings, property details, pricing estimates, or typical real-estate workflows. Even viewed as a broad data platform, the set is read-heavy with no create/update/delete operations beyond memories and subscriptions, leaving significant workflow gaps.

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