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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

A4.5/5.0
Behavior5/5

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

The description is extremely transparent, disclosing caching behavior ('Cached 1h at the KV level keyed on all knobs'), the logic behind model families (e.g., 'lognormal barrier from 90d FRED log-returns'), edge calculation ('net of slippage'), and output structure ('by_segment{...}, fed_candidates, _diagnostics'). It goes far beyond the annotations, which only indicate read-only and idempotent traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is verbose, with detailed explanations of model families and internal calculations. While front-loaded with the purpose, it could be more concise. The depth is understandable given the tool's complexity, but it could be structured more efficiently for quick scanning.

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 return structure (by_segment segments, fed_candidates, _diagnostics) and the contents of each opportunity (edge_pp_net, kelly_fraction, etc.). It also covers caching, exclusion of Fed bets, and the rationale behind knobs. This provides complete context for an agent to use the tool effectively.

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 coverage is 100% with detailed parameter descriptions. The description adds extra meaning, such as explaining that 'min_liquidity' and 'max_spread_pp' are 'Tradeable-edge filters' and providing default values and reasoning (e.g., 'bump for very thin partitions'). This adds value beyond the schema, warranting a score above the baseline of 3.

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: 'Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price.' It uses a specific verb ('scan' and 'return') and resource ('Polymarket markets') and distinguishes from siblings like polymarket_arbitrage and polymarket_edge_tracker by focusing on edge detection from Pipeworx data.

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 says it's 'Built for 'what should I bet on today' — agents discover opportunities without paging hundreds of markets.' It provides context on when to use it (discovery) but does not explicitly mention when not to use or alternatives. However, the detail on model families and tradeable-edge knobs helps the agent understand appropriate usage scenarios.

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

A3.5/5.0
Disambiguation2/5

Several tools have near-identical or heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx and validate_claim both answer factual questions, and discover_tools and suggest_questions both surface capabilities. The dense set of Polymarket and entity-research tools further blurs boundaries despite long descriptions.

Naming Consistency3/5

Names are consistently snake_case, but they do not follow a single predictable verb_noun pattern: actionable names like ask_pipeworx, search_projects, and compare_entities mix with noun-style names like polymarket_edges, pipeworx_feedback, and recent_changes. The convention is readable but not uniform.

Tool Count2/5

34 tools exceeds the reasonable scope for a coherent server, and many are near-duplicate variants or members of sprawling tool families (ask_pipeworx variants, multiple Polymarket scanners, several meta/discovery tools). The set would be stronger with consolidation around a smaller number of distinct capabilities.

Completeness1/5

If this server is meant to provide OSF access, the surface is severely incomplete: only search_projects, search_preprints, and get_project exist, with no create/update/delete, file handling, registration, or contributor access. If it is meant to be a broader Pipeworx assistant, the OSF tools are unrelated and the domain is so scattered that coverage is incoherent.

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