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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?

Annotations show readOnlyHint, openWorldHint, idempotentHint true, and destructiveHint false. The description adds substantial behavioral context beyond these: it explains monotonicity checks, partition-sum validation, semantic anchor filtering, placeholder handling, and fill check integration. There is 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 quite detailed and well-structured with clear sections for modes, semantic anchor, partition filter, response, and fill check. While it is lengthy, every sentence adds value, and the first sentence is a concise purpose statement. Minor deduction for not being more front-loaded; could be slightly more compact.

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 (multiple modes, sub-checks, integration with another tool), the description is highly complete. It explains the response format (opportunities array with gap_pp, suggested_trade, reasoning, etc.) and details the partition check and fill check behavior, compensating for the absence of an output schema.

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% (both parameters have descriptions), and the tool description adds significant meaning: for 'event', it explains how to use event slugs and that full URLs are accepted; for 'topic', it explains cross-event scanning with a seed question. This goes well beyond the schema's minimal 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 different modes (no args, event, topic) with distinct resources, effectively distinguishing this tool from siblings 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?

Explicit guidance is given for when to use each mode: call with no args for a trending scan of top markets, pass 'event' for a specific event slug, or pass 'topic' for cross-event scanning. It also provides conditions like Jaccard similarity threshold and partition filter, and even advises against trading when realizable_edge_pp ≤ 0, referencing 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

A3.8/5.0
Disambiguation2/5

Several clusters of tools are hard to tell apart: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve overlapping query paths, and the five polymarket_* tools plus bet_research cover heavily overlapping prediction-market analysis. Some pairs are nearly identical in purpose, like ai_visibility_check vs scan_competitor_ai_presence, and the descriptions must be read closely to avoid misselection.

Naming Consistency2/5

All names are snake_case, but the naming style is highly inconsistent across the set: some use verb_noun (ask_pipeworx, generate_llms_txt, resolve_entity), some are noun phrases (entity_profile, pipeworx_feedback, recent_alerts), and some use a vendor prefix without a clear verb (polymarket_edges, polymarket_edge_tracker). The pattern shifts between domain-specific prefixes (polymarket_*, pipeworx_*) and generic verbs with no predictable rule.

Tool Count2/5

32 tools is too many for a cohesive server, especially when the surface sprawls across unrelated domains: data querying, prediction markets, memory, subscriptions, npm scanning, AI visibility checks, and llms.txt generation. Many tools could be consolidated (the ask_pipeworx family, the polymarket family, the entity-comparison family), which would make the count feel more justified.

Completeness4/5

Within its apparent purpose as a broad data-and-research assistant, the tool set is fairly complete: it covers entity resolution, lookup, grounded verification, deep research, comparisons, memory CRUD, subscription lifecycle, discovery, and feedback. Minor gaps exist, such as no direct tool to fetch a record by its pipeworx:// citation URI (search_within implies fetching happens elsewhere) and no evident update operation for stored memories beyond save/delete.

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