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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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds extensive behavioral context: how arbitrage detection works (monotonicity violations, partition checks), semantic anchor for cross-event pairs (Jaccard threshold), partition filter (placeholder slugs), and fill check logic (theoretical vs realizable edge). This goes well beyond 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 thorough and well-structured with clear sections (SEMANTIC ANCHOR, PARTITION FILTER, FILL CHECK). It is somewhat verbose but every sentence adds value given the tool's complexity. Front-loaded with the core purpose.

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 no output schema or nested objects, the description fully explains return fields (opportunities, partition_check, fill check details), error conditions (low similarity, placeholder fraction >20%), and references sibling tool (polymarket_fill_risk) for custom sizing. Highly complete for a complex tool.

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 mode walks child markets and checks multiple conditions, topic mode searches related events and runs comparator, and provides examples of valid inputs (e.g., 'fed-decision-may-2026'). The no-argument behavior (trending scan) is also clarified.

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 finds arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It specifies three distinct modes (no args, event, topic) and differentiates from siblings like polymarket_fill_risk, making the purpose highly specific and distinguishable.

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 explicit guidance on when to use each mode (no args for trending scan, event for specific market, topic for cross-event scan) and recommends event for specific markets. It also explains when not to trade (if realizable edge ≤ 0). However, it does not directly compare to sibling tools, just within its own modes.

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

A3.7/5.0
Disambiguation2/5

The set mixes Salesforce CRUD tools with a large Pipeworx research and prediction-market platform, and several tools overlap heavily: ask_pipeworx vs ask_pipeworx_beta are functionally identical, grounded/validate_claim/deep_research cover similar lookup/verification territory, and the six polymarket/bet tools share edge-finding purposes with only subtle distinctions. An agent would need to read long descriptions carefully to pick the right one, so misselection risk is high.

Naming Consistency3/5

Salesforce tools follow a clear sf_verb_noun pattern, and the Pipeworx tools mostly use lowercase snake_case phrase names, but the conventions diverge: ask_pipeworx has no underscore, deep_research/entity_profile are noun phrases rather than verb-first, and the sf_* prefix is a separate naming family. It is still readable, but it is not a single predictable pattern.

Tool Count2/5

39 tools is well past the heavy threshold, and most belong to a broad data/research platform rather than the Salesforce scope implied by the server name; only 8 tools are actually Salesforce CRUD/query operations. The count feels bloated for a coherent assistant, even if individual features are useful.

Completeness4/5

The Salesforce subset is complete: create/get/update/delete/query/search/describe/list-object cover the record lifecycle with no dead ends. The broader Pipeworx ecosystem also has strong coverage, including routing, grounded verification, research, entity resolution, memory, and subscriptions, with only minor gaps such as no direct citation-fetch tool and no Salesforce upsert/bulk operations.

Resources