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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 tool is annotated as readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context: snapshots are written on cache-miss (so gaps in data mean no one scanned that day), history is bounded by a 60-day TTL, and decay numbers are based on daily closes (net of default slippage). This goes well beyond the annotations and fully discloses relevant behaviors.

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 comprehensive but well-structured: it starts with the core purpose, then explains each response field in detail, and ends with limits. Every sentence adds value, though it could be slightly more concise. Overall, it's appropriately sized for the complexity of the tool.

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 that there is no output schema, the description fully describes the response structure: tracked[], expired[], snapshot_dates[], and explains each field (first_seen, trend, decay_pp_per_day, lifespan_days, etc.). It also covers limits and data gaps. For a tool with two simple parameters, this is exceptionally complete and leaves no ambiguity.

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?

The input schema already describes both parameters with 100% coverage. The description adds meaning by stating the default and valid range for 'days' (default 14, max 30) and the default for 'window' ('1wk'). This provides useful context beyond the schema, justifying a score above 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 title and first sentence clearly state that this tool provides edge persistence and decay telemetry from daily snapshots. It answers 'how long has this edge existed and is it shrinking?', which is specific and distinct from sibling tools like polymarket_edges (current snapshot) or polymarket_arbitrage (arbitrage opportunities). The description goes into detail about the response fields, further clarifying its purpose.

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 provides context for when to use this tool: when you need to distinguish between a fresh wide edge and an old one (the latter is wide for a reason nobody is willing to take). It also explains limits like the 60-day snapshot TTL and that decay numbers are from daily closes, not intraday. It does not explicitly say when not to use this tool or name alternatives, but the sibling context and description imply it's for historical analysis vs. 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

Tools are mostly distinct in purpose but some overlaps exist, e.g., multiple ask_pipeworx variants and several polymarket analysis tools. Detailed descriptions help, but the sheer variety and similar intent of some tools could confuse agents.

Naming Consistency2/5

Naming is highly inconsistent: snake_case (ai_visibility_check), single words (forecast), action_noun (bet_research), prefixes (polymarket_, pipeworx_), and descriptive phrases (scan_competitor_ai_presence). No uniform pattern.

Tool Count2/5

33 tools is too many for a server named 'Pirate Weather' that only has two weather-specific tools. The tool count feels inflated with many meta-tools and unrelated domains, exceeding a coherent scope.

Completeness2/5

Coverage is incomplete for the implied weather focus (only two tools). Other domains like prediction markets are better covered, but overall the surface is a mix of partial offerings with clear gaps (e.g., no update/delete for subscriptions).