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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

A4.7/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive. The description adds rich behavioral context: it reads from snapshots, computes trends and decay, returns expired opportunities with lifespan, explains data gaps on cache-miss days, and details the signed nature of edge_pp_net. 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 somewhat long but well-structured: first sentence states purpose, then details response fields with clear formatting, and ends with limitations. Every sentence adds value, though some could be tightened. The structure aids readability.

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 thoroughly explains the response fields (tracked, expired, snapshot_dates) and their meanings. It covers data limitations (TTL, snapshot gaps) and provides enough context for an agent to understand the tool's behavior. No missing critical aspects.

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%, but the description adds meaning: explains days as lookback with defaults and clamping, window as snapshot family with defaults, and describes how these affect the returned data (e.g., number of snapshots). It also details the response structure, which is not in the schema.

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 it provides 'edge persistence and decay telemetry' from daily snapshots, answering specific questions about edge longevity and shrinkage. It distinguishes from siblings like polymarket_edges by focusing on historical trend vs current snapshot.

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 explains when to use this tool (to understand edge history and decay) and provides context about fresh vs old edges. It doesn't explicitly state when not to use or list alternatives, but the purpose is clear enough. Implicitly, polymarket_edges is the alternative for current data.

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

A3.6/5.0
Disambiguation2/5

Multiple tools overlap conceptually, e.g., ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded / deep_research all perform data retrieval, and bet_research / polymarket_edges / polymarket_arbitrage cover prediction markets with unclear boundaries. This overlap forces agents to carefully read descriptions to pick the right tool.

Naming Consistency3/5

Naming is mostly snake_case but inconsistent in pattern: some are verb_noun (compare_entities), some are noun_verb (ai_visibility_check), and some are bare nouns (ipv4) or bare verbs (forget). While readable, the lack of a uniform pattern reduces predictability.

Tool Count2/5

33 tools is high for a single server, especially given the server name 'Ipify' which implies a simple IP lookup service. The broad range (from memory ops to prediction market analysis) suggests the tool set is a collection of utilities rather than a coherent, scoped API.

Completeness2/5

The tool set lacks focus: for a server named 'Ipify', basic IP geolocation or ASN lookup is missing. As a general toolkit, it covers many areas superficially but has significant gaps (e.g., no tools for updating or deleting data, no domain-specific lifecycle).