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Entertainment Feeds

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

A5/5.0
Behavior5/5

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

Annotations (readOnlyHint=true, destructiveHint=false) already indicate safety. The description adds substantial behavioral details: algorithms used (monotonicity, partition checks), semantic anchor (Jaccard similarity), partition filter (placeholder slugs), fill check (theoretical vs realizable edge), and explicit advice not to trade when realizable edge ≤ 0. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections for each mode and sub-mechanisms. Though long, every sentence adds unique value—no filler or redundancy. Information is front-loaded with the primary purpose and usage guidance.

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 the lack of an output schema, the description fully explains the response structure (opportunities array with fields, partition_check object, fill check details). It also covers edge cases (default behavior, topic mode limitations, when not to trade). For a complex tool, the description is thorough and sufficient.

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% but the description adds significant meaning: it explains that 'event' expects Polymarket event slugs like 'fed-decision-may-2026' and that 'topic' expects a seed question. It also clarifies the default behavior when neither parameter is provided. This goes well beyond the schema 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: finding arbitrage opportunities on Polymarket via monotonicity violations and partition-sum checks. It distinguishes between two modes (event and topic) and describes the default trending scan. The purpose is specific and verifiable.

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 when to use each parameter: '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 and topic for cross-event scanning. It also mentions an alternative tool (polymarket_fill_risk) 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

A3.6/5.0
Disambiguation3/5

While most tools have distinct purposes, there is notable overlap between the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and deep_research. Similarly, bet_research and polymarket_edges both analyze betting opportunities. These overlapping tools can cause confusion for an agent.

Naming Consistency2/5

Tool names follow a snake_case pattern, but the verbs used are highly varied (ask_, bet_, compare_, deep_, discover_, entity_, fetch_, forget_, generate_, list_, pipeworx_, polymarket_, read_, recall_, recent_, remember_, resolve_, scan_, search_, subscribe_, suggest_, unsubscribe_, validate_). This lack of a consistent verb_noun pattern makes it harder to predict tool names.

Tool Count2/5

34 tools is excessive for an 'Entertainment Feeds' server. The majority of tools are unrelated to entertainment (e.g., SEC filings, FDA drugs, FRED data, Polymarket betting). Many of these should belong to a separate 'data-access' server, making the scope unwieldy and unfocused.

Completeness2/5

For an entertainment feeds server, the set is incomplete. It can list and read curated feeds and fetch arbitrary RSS, but lacks tools for managing subscriptions to those feeds, searching across feeds, or creating feeds. The inclusion of many non-entertainment tools doesn't compensate for these gaps.

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