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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

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description adds behavioral details like semantic anchor (Jaccard similarity >= 0.30), partition filter (placeholder fraction >20% returns null), and fill check against live CLOB depth. 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 verbose but well-structured with bolded section headers (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK). It front-loads the main purpose and argument options. A minor reduction in redundancy could improve conciseness.

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's complexity and lack of output schema, the description covers all key aspects: three modes, internal logic (semantic anchor, partition filter, fill check), response structure (opportunities[], partition_check), and even a reference to a related tool. It is complete and self-contained.

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 are described in the schema, but the description adds extensive meaning: for 'event' it explains walking child markets and checks; for 'topic' it explains searching related events and flattening markets. Examples of slugs and seed questions are provided, making the parameters much clearer.

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: finding arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It distinguishes three modes (default, event, topic) with specific descriptions of each, and contrasts with sibling tools like 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 explicitly explains when to use each argument: no args for trending scan, 'event' for specific market partition check, 'topic' for cross-event scanning. It also warns when not to trade (realizable_edge_pp ≤ 0) and suggests an alternative tool for custom sizing.

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

B3.4/5.0
Disambiguation2/5

The vast majority of tools are unrelated to GitLab and cover overlapping domains (multiple ask_pipeworx variants, several Polymarket tools, memory tools). Only three GitLab-specific tools exist, and they are distinct from each other, but overall the set is highly heterogeneous and ambiguous.

Naming Consistency2/5

Tool names use a mix of conventions: some are snake_case (ask_pipeworx, search_issues), some are compound nouns (get_project, list_subscriptions), and a few are single words (forget, recall). There is no consistent pattern, making it harder to predict tool names.

Tool Count1/5

Despite the server name 'Gitlab Public', only 3 out of 34 tools are related to GitLab. The remaining 31 tools are a collection of unrelated services (Pipeworx data retrieval, Polymarket betting, memory, AI visibility). This is a severe mismatch between the server's stated purpose and its tool composition.

Completeness1/5

For a GitLab public server, essential tools like project creation, deletion, user management, and merge request handling are completely missing. The Pipeworx tools, while numerous, lack a clear cohesive scope and overlap significantly with each other.

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