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Warframe

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

A5/5.0
Behavior5/5

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

Even though annotations already declare readOnlyHint and idempotentHint, the description adds deep behavioral context: it explains the partition_check threshold (deviations >3pp), the semantic anchor (Jaccard ≥0.30), the placeholder filter, and the fill check with realizable_edge_pp ≤ 0 meaning 'do not trade it'. 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 long but tightly structured: first sentence states core purpose, then a quick mode overview, followed by mode-specific details, edge cases, and response format. Each sentence earns its place—there is no fluff or repetition, and key details like FILL CHECK and PARTITION FILTER are clearly labeled.

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?

With no output schema, the description fully discloses return values: 'opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context)' and 'partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}'. It also covers edge cases (placeholders, low similarity, book depth) and explicitly states the condition under which an arbitrage should not be traded, making the tool 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?

While the schema descriptions for event and topic are basic, the tool description vastly expands their meaning: it gives concrete slug examples (e.g., 'fed-decision-may-2026'), explains what each mode does internally, and even defines the no-arg trending_scan behavior. This goes well beyond the schema's 100% coverage.

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 verb+resource+method: 'Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks.' It clearly distinguishes this tool from siblings like polymarket_edges and polymarket_fill_risk by explaining the core techniques and then enumerating three distinct invocation modes.

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 scenario-driven: '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, topic for cross-event, and points to polymarket_fill_risk for custom sizing, effectively saying when to use this tool vs. an alternative.

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

Many tools overlap in purpose: three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are nearly identical routers, five polymarket_* tools cover similar prediction-market ground, and the server combines a tiny Warframe component with a broad Pipeworx/Polymarket toolkit, making selection ambiguous. The server name 'Warframe' does not match the majority of tools, further muddying intent.

Naming Consistency3/5

There is a loose snake_case convention, and several tools follow a verb_noun pattern (get_fissures, list_subscriptions, search_items, validate_claim). However, single-word imperative tools (remember, recall, forget), noun-phrase names (entity_profile, world_state, deep_research), and the polymarket_* family using inconsistent second words break the pattern. It is readable but not cleanly predictable.

Tool Count2/5

35 tools is far too many for a Warframe-focused server, and only 4 tools (get_fissures, get_invasions, search_items, world_state) actually relate to Warframe. The remaining 31 tools are a sprawling generic data/research/prediction-market collection that belongs to a different product, making the set bloated and unfocused for its apparent purpose.

Completeness3/5

Relative to the Warframe domain, the coverage is thin: only fissures, invasions, item search, and a combined world_state are offered, with obvious gaps like alerts, news, Nightwave, and event tracking. The broader Pipeworx/Polymarket toolset is internally comprehensive, but those tools do not serve the server's stated name and leave the Warframe scope incomplete.

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