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Guild Wars 2

by io.github.pipeworx-io

Polymarket Edges

polymarket_edges
Read-onlyIdempotent

Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by_segment: (1) MODEL_DRIVEN — crypto_price (lognormal barrier from 90d FRED log-returns) and news_momentum (GDELT 7d/21d article-volume ratio, soft signal w/ halved Kelly). (2) STRUCTURAL_ARBITRAGE — partition_overround on mutually-exclusive events; per-leg favorite-longshot bias correction with per-sport α (tennis 1.02, soccer 1.10, MMA 1.15, default 1.0); placeholder-slug filter drops will-person-X / will-team-Y / will-manager-Z / will-someone-else- backstops; partitions with >20% placeholder fraction skipped entirely. (3) CONCENTRATED_LONGSHOT — basket trade when one leg ≥75% AND ≥2 longshots ≤8% AND portfolio return ≥25:1; rare-by-design (gates relaxed Run 8 from prior 85%/5%/50:1). EVERY OPPORTUNITY carries edge_pp_net (after slippage), kelly_fraction + kelly_fraction_half (capped at 0.25), market.liquidity, market.spread_pp, market.volume, plus a 24h-move warning ("Market moved X.Xpp in 24h") when the recent move alone exceeds the edge — your edge may already be in the price. TRADEABLE-EDGE KNOBS: min_liquidity / max_spread_pp drop opportunities where edge isn't realizable; min_partition_leg_kelly filters partitions by best per-leg Kelly. RESPONSE TOP-LEVEL: by_segment{model_driven,structural_arbitrage,concentrated_longshot}, fed_candidates/fed_note (Fed bets surface here, excluded from ranking — 1m-T vs EFFR signal is unreliable at meeting-month horizons without paid OIS/SOFR-futures data), and _diagnostics{concentrated_longshot:{...funnel counters},category_counts,filter_skips} so callers can see WHY a segment is empty (top-N stale, all candidates failed gates, knob dropped them). Cached 1h at the KV level keyed on all knobs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoTop N edges to return after ranking. Default 10, max 25.
windowNoPolymarket volume window to filter markets. Default 1wk.
min_kellyNoMinimum half-Kelly fraction (as decimal, e.g. 0.005 = 0.5% of bankroll) to include single-leg opportunities. Default 0 (no filter). Skips opportunities that are too small to bet sensibly even if the edge is large.
min_edge_ppNoMinimum |edge| in percentage points to include (default 0.5). Edge is evaluated NET of slippage.
slippage_ppNoAssumed execution slippage in percentage points per leg (default 0.3). Subtracted from raw |edge| before ranking and Kelly sizing. Polymarket has zero trading fees as of 2024 but bid/ask + thin depth typically eats 20-50bp per trade. Bump for very thin partitions; drop to 0 if you have a smarter fill model.
max_spread_ppNoTradeable-edge filter. Maximum bid/ask spread in percentage points on the representative market. Default null (no filter). Set to 2 to require tight books — anything wider eats most plausible edges.
min_liquidityNoTradeable-edge filter. Minimum $ liquidity on the representative market (or for partition_overround, on at least one top_leg). Default 0 (no filter). Set to 5000 to drop thin-book opportunities where executing the edge would walk the book past breakeven.
category_filterNoComma-separated list to restrict the output: "model_driven" (crypto_price + news_momentum), "structural_arbitrage" (partition_overround), "concentrated_longshot". Combine like "model_driven,structural_arbitrage". Default: all.
min_partition_leg_kellyNoMinimum BEST per-leg half-Kelly fraction across a partition_overround opportunity's top_legs (or longshot_basket legs). Default 0 (no filter). Partition arbs always return kelly_fraction_half=0 at the parent level by design (basket trades don't compose to single-leg Kelly), so min_kelly never filters them — this knob applies to the per-leg Kelly inside top_legs instead. Use to suppress thin partitions whose individual leg edges aren't worth the per-leg slippage cost.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and other safety cues. The description adds extensive behavioral context: cache duration (1h), response structure (by_segment with three model families), edge computation details, and diagnostics for empty segments. 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 lengthy but well-organized, with numbered segments and clear sections for knobs and diagnostics. Every sentence adds value given the tool's complexity. Could be slightly tighter, but front-loads purpose effectively.

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?

With 9 parameters, no output schema, and complex nested response structure, the description compensates fully. It explains the three response segments, fed_candidates, diagnostics, and how parameters like min_partition_leg_kelly affect filtering. Complete enough for agent invocation.

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 provides 100% parameter descriptions with decent detail. The description adds semantic connections, e.g., why min_partition_leg_kelly exists (partition arbs always return kelly_fraction_half=0 at parent level). This adds meaning beyond the schema's per-parameter docs.

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 scans Polymarket markets for opportunities where Pipeworx disagrees with market price, with a specific use case ('what should I bet on today'). It distinguishes from sibling tools like polymarket_arbitrage and polymarket_edge_tracker by focusing on edge discovery without paging.

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 explicitly states the tool is for discovering opportunities and avoiding manual paging. It implies context (daily betting scouting) but does not explicitly list alternatives or when not to use. Sibling names suggest related tools, but no direct comparisons are made.

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

C2.8/5.0
Disambiguation2/5

The set mixes two unrelated domains (Guild Wars 2 endpoints and a broad Pipeworx data-research suite), and within each there are near-duplicates: ask_pipeworx vs ask_pipeworx_beta are functionally identical, commerce_prices vs guild_wars_2_item_price vs commerce_listings overlap on Trading Post data, and ask_pipeworx/ask_pipeworx_grounded/deep_research all route questions to the same source catalog. An agent could easily select the wrong tool.

Naming Consistency3/5

Names are all snake_case and readable, but there is no consistent pattern: some are bare nouns (achievements, currencies, quaggans, worlds, build), some are verb_noun (resolve_entity, validate_claim, generate_llms_txt), some are ask_* (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and some are compound names (polymarket_kalshi_spread, guild_wars_2_item_price). Minor deviations would be fine, but this is a genuine mix of conventions.

Tool Count2/5

42 tools is far beyond the well-scoped range, and the majority are unrelated to the 'Guild Wars 2' server name (only ~11 tools are GW2 API endpoints; the rest are Pipeworx data-research/meta tools). This feels like two or three servers merged into one.

Completeness2/5

For a Guild Wars 2 server, the coverage is thin: it has items, prices, achievements, worlds, and WvW, but no recipes, guilds, characters, skills, maps, or PvE content. For the broader data-research domain implied by most tools, the surface is sprawling but still lacks depth in several areas. The result is a set that is neither complete for GW2 nor coherently scoped for anything else.

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