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Textcase

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

A4.8/5.0
Behavior5/5

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

Annotations (readOnlyHint, openWorldHint, idempotentHint) already indicate safety and non-destructiveness. The description adds detailed behavioral insights: the FILL CHECK logic, SEMANTIC ANCHOR (Jaccard similarity), PARTITION FILTER, and what realizable_edge_pp ≤ 0 means. This goes well beyond annotations, disclosing when not to trade.

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 well-structured into modes and sub-sections, with brief but informative sentences. Each sentence adds value. However, some phrasing is slightly verbose (e.g., 'use this if you know the specific Polymarket event') and could be tightened.

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 having no output schema, the description thoroughly documents the response format (opportunities[] with fields, partition_check with fields, fill_check results). It covers all modes, internal checks, and caveats, making it complete for an agent to correctly invoke and interpret results.

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% (both parameters described). The description adds significant value by explaining the semantics of each parameter, providing examples ('fed-decision-may-2026'), and clarifying behavior when no arguments are passed (triggers trending_scan). This enriches understanding 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 action, resource, and method, and distinguishes between modes (trending_scan, event, topic). This differentiates it from sibling tools like polymarket_edges or 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?

The description 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.' It recommends `event` for specific markets and `topic` for cross-event scanning, and even redirects to an alternative: 'For custom sizing use polymarket_fill_risk.'

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

Several tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to data sources; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread, and bet_research all target prediction-market analysis; and all_cases plus convert_case both handle text-case conversion. An agent will struggle to pick the right tool without deep reading.

Naming Consistency3/5

Nearly all names are lowercase with underscores, but the morphological pattern is mixed: some are verb_noun (convert_case, compare_entities, resolve_entity, scan_dependency), many are bare nouns (entity_profile, pipeworx_trending, polymarket_edges, all_cases), and a few are single-word verbs (forget, recall, remember). Still readable, but not a predictable verb_noun convention throughout.

Tool Count2/5

33 tools is far too many for a server named 'Textcase' — only all_cases and convert_case relate to the apparent purpose. The remaining 31 constitute a sprawling assortment of data research, prediction markets, memory, subscriptions, and feedback tools that have nothing to do with text casing, making the count feel bloated and misaligned.

Completeness2/5

For the stated text-case domain, the two converters cover the basic transformations but lack supporting operations like case detection, batch processing, or custom case definitions. More fundamentally, the tool surface is incoherent: the majority of tools serve foreign domains (Pipeworx data, Polymarket, subscriptions), so there is no clear domain to evaluate for completeness, and obvious gaps exist within whatever the server is meant to be.

Resources