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Polymarket Edge Tracker

polymarket_edge_tracker
Read-onlyIdempotent

Edge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: days (lookback, default 14, max 30), window (snapshot family, default "1wk"). RESPONSE: tracked[] = every opportunity in the LATEST snapshot with its full edge_pp_net time-series across prior snapshots, first_seen, trend (new | widening | stable | decaying) and decay_pp_per_day (both computed on |edge_pp_net| — the value itself is signed by trade direction, negative = SELL YES); expired[] = opportunities that appeared in earlier snapshots but are GONE from the latest (closed, resolved, or arbed away) with their lifespan_days — the median lifespan is your competition clock; snapshot_dates[] = which days actually have data (snapshots are written when polymarket_edges runs on a cache-miss, so gaps mean nobody scanned that day). LIMITS: history depth is bounded by the 60-day snapshot TTL and starts from when snapshotting was enabled; decay numbers come from daily closes of edge_pp_net (net of default slippage), not intraday.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback in days (default 14, clamp 2-30).
windowNoWhich polymarket_edges window family to read snapshots for: 24hr | 1wk | 1mo (default 1wk).

Schema Changelog

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

  1. Added
  2. Removed
  3. Added

TDQS

A4.6/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations, including history limits (60-day TTL), decay calculation from daily closes, snapshot gaps due to cache-miss, and a detailed breakdown of the response structure.

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 thorough and front-loaded with the core purpose, but it is somewhat dense. Each part adds value, though it could be slightly more concise without losing 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?

Given no output schema, the description comprehensively explains the return values (tracked, expired, snapshot_dates) and covers edge cases like gaps and limitations, providing complete context for using the tool.

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 parameter descriptions, but the description adds context such as default and max for `days`, and explains `window` as a snapshot family, enhancing understanding of how parameters affect data retrieval.

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 provides edge persistence and decay telemetry, distinguishing it from the sibling `polymarket_edges` by focusing on historical behavior rather than current edges.

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 implies usage for deciding whether to act on an edge based on its age, and contrasts fresh vs. old edges. While it does not explicitly state when not to use it, the context and sibling list indicate `polymarket_edges` is the alternative for current edges.

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

B3.1/5.0
Disambiguation3/5

Several tool families overlap heavily: ask_pipeworx, its beta, and grounded variants, the six polymarket_* tools, and the three price endpoints (price, price_full, price_multi) can be confused despite distinct purposes. Long descriptions provide some disambiguation, but an agent must read carefully to select the correct tool.

Naming Consistency4/5

Tool names mostly follow snake_case with verb_noun or noun_noun patterns (all_coins, compare_entities, top_market_cap), and related families share clear prefixes (histo_*, polymarket_*). Minor deviations exist (bare verbs like remember/forget, brand names like ask_pipeworx), but the overall pattern is readable and consistent.

Tool Count2/5

With 46 tools, the server is far beyond the 3-15 well-scoped range and nearly double the 25-tool threshold for 'too many'. Many tools are unrelated to the server's apparent crypto purpose (generate_llms_txt, scan_dependency, memory helpers), making it feel like a general-purpose utility rather than a focused data service.

Completeness3/5

The crypto data surface is fairly complete (spot, historical, top lists, news, social stats, exchange metadata), and the Pipeworx meta-tools (ask_pipeworx, deep_research, entity_profile) cover a broad range of factual queries. However, there are notable gaps: no direct way to fetch pipeworx:// citation URIs, and no advanced crypto order-book/trade endpoints, leaving some workflows as dead ends.