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Bungie

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, destructiveHint=false. Description adds rich behavioral context: scanning top 200 markets, Jaccard similarity threshold, placeholder filter, fill check against CLOB depth. No contradictions.

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?

Well-structured with front-loaded purpose and clear parameter breakdown. However, the description is dense and could be slightly more concise while retaining all essential details.

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?

No output schema, so description must cover return values. It does: lists fields of opportunities array and partition_check object, explains fill_check. For a 2-param tool, this is comprehensive.

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%, baseline 3. Description adds significant semantics: explains event slug/URL acceptance, topic as seed question, behavior for each mode (including default no-arg behavior). Provides recommendations and mode-specific outcomes.

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 states a specific verb and resource ('Find arbitrage opportunities on Polymarket') with clear method ('monotonicity violations + partition-sum checks'). It distinguishes from sibling tools like polymarket_edges and polymarket_fill_risk by focusing on arbitrage detection via these specific checks.

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?

Explicitly states when to use each parameter: no args for trending scan, event for per-event partition check, topic for cross-event scan. Recommends event mode for specific markets. Warns against trading when realizable_edge_pp ≤ 0. Provides alternatives for custom sizing (polymarket_fill_risk).

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

C2.7/5.0
Disambiguation3/5

The tool set mixes Destiny 2 game tools with a large suite of general data querying tools from Pipeworx. Within the data querying subset, tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research have overlapping purposes, making it hard for an agent to distinguish which to use. The Destiny tools are more distinct, but overall, the set has noticeable ambiguity.

Naming Consistency2/5

Tool names are highly inconsistent, mixing single-word names (character, clan), snake_case (ask_pipeworx, deep_research), and compound names with underscores (polymarket_arbitrage, scan_dependency). There is no uniform verb_noun or other predictable pattern, making it difficult for an agent to infer functionality from the name alone.

Tool Count2/5

With 43 tools, the server is bloated for its stated name 'Bungie'. Many tools are unrelated to Bungie (e.g., Pipeworx data tools, Polymarket tools), suggesting the server aggregates multiple domains without clear scoping. The tool count is too high for a coherent set focused on a single service.

Completeness2/5

For the Bungie game domain, the set is fairly complete (characters, clans, stats). However, the inclusion of numerous unrelated tools (financial, economic, prediction market) fragments completeness. The server lacks a clear domain, leaving gaps in both the Bungie-specific and the general data querying aspects when considered as a unified set.

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