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Medical Codes

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 already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds extensive behavioral detail: internal checks (semantic anchor with Jaccard similarity, partition filter, fill check against CLOB depth), response structure, and edge cases (skipped_low_similarity, placeholders_filtered). 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 detailed and well-structured, front-loading the core purpose and then expanding on modes and internal logic. Every sentence adds value, but the length is somewhat high; some internal details (e.g., Jaccard similarity threshold, placeholder fraction) could be streamlined without loss of clarity. However, for a complex tool, this is acceptable.

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, the description thoroughly explains the response format: 'opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{...}.' It covers all three modes, internal checks, and edge cases. The tool is non-trivial, and the description provides complete contextual coverage.

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 descriptions for both parameters. The description greatly enriches meaning: explains the difference between event and topic modes, provides concrete examples ('fed-decision-may-2026', 'Strait of Hormuz traffic returns to normal'), and notes that full Polymarket URLs are accepted for event. This goes well beyond the schema.

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 distinguishes three distinct modes (no args, event, topic) and differentiates from siblings by focusing on arbitrage detection, as seen in sibling list with related but distinct tools like polymarket_edges and 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 provided for each mode: 'Call with NO args for a trending_scan...', 'event (recommended for a specific market)', 'topic (for cross-event scanning).' It explains when not to trade (realizable_edge_pp ≤ 0) and points to an alternative tool: 'For custom sizing use polymarket_fill_risk.' This covers when, when-not, and alternatives.

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
Disambiguation3/5

While most tools have detailed descriptions, the large number of similar data-querying tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, bet_research, etc.) and overlapping domains (Polymarket, company research, medical) create ambiguity for an agent.

Naming Consistency2/5

Tool names mix conventions: snake_case (ai_visibility_check, ask_pipeworx), camelCase absent, some with 'pipeworx' prefix, others not (bet_research, compare_entities). No consistent verb_noun pattern.

Tool Count1/5

33 tools for a server named 'Medical Codes' is excessive and misaligned. The vast majority of tools cover unrelated domains (finance, prediction markets, general research), making the count inappropriate for the stated purpose.

Completeness1/5

For medical coding, only three tools exist (search_icd10, search_loinc, search_medical_terms). The rest are tangential or unrelated, leaving severe gaps in medical code coverage.

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