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Biosamples

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations indicate read-only, open-world, idempotent, non-destructive behavior. Description adds extensive context: partition checks, semantic anchor for cross-event, placeholders filter, fill check against live order book depth. 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?

Description is detailed but well-structured with distinct sections for each mode and important notes. Could slightly trim redundancy, but it remains readable and front-loaded with key information.

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 (three modes, multiple checks), the description is exceptionally thorough, covering response structure, semantic constraints, and edge cases like placeholder filtering. No output schema, but response fields are enumerated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, providing clear descriptions for both parameters. Description adds extra meaning: event accepts full URLs, topic is a seed question, and explains the mode behavior in depth.

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 distinguishes three modes (no args, event, topic) with specific verbs and resources.

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 describes when to use each mode: no args for trending scan, event for specific market, topic for cross-event scan. Also advises when not to trade (realizable_edge_pp <= 0) and provides alternatives like 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

A3.8/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and ask_pipeworx_grounded is a subtle behavioral variant, creating a real selection hazard. The six polymarket_* tools also blur together (edges vs arbitrage vs fill_risk vs kalshi_spread all relate to finding and acting on mispricings), and scan_competitor_ai_presence is largely a wrapper over ai_visibility_check.

Naming Consistency3/5

All names are snake_case and several families share clear prefixes (ask_pipeworx, polymarket_*, pipeworx_*, scan_*), which keeps the set readable. However, the set mixes verb-first names (get_sample, compare_entities, resolve_entity) with noun-first names (entity_profile, bet_research, recent_changes, polymarket_edges), and the _beta suffix signals a status while _grounded signals a behavior, so the pattern is not predictable.

Tool Count2/5

33 tools is above the threshold where a tool set starts to feel bloated, and for a server named 'Biosamples' it is an extreme scope mismatch: 31 of 33 tools relate to Pipeworx data routing, prediction markets, memory, or subscriptions rather than biological samples. The count is also padded with near-duplicates such as ask_pipeworx_beta and scan_competitor_ai_presence.

Completeness2/5

Against the server's stated identity, the BioSamples surface is severely thin: only search_samples and get_sample exist, with no batch retrieval, project/group navigation, sample-group hierarchy, or submission/update path. The 31 unrelated tools do not fill this gap — they serve a completely different domain, so an agent using this server for biological sample data will hit dead ends.

Resources