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by io.github.pipeworx-io

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?

The description adds significant behavioral context beyond annotations: it explains the response structure (tracked, expired, snapshot_dates), that data is based on daily closes, that gaps occur on cache-miss days, and that decay is computed from absolute edge values. Annotations already indicate read-only and idempotent, and description reinforces these.

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 dense and informative but slightly verbose. It front-loads the core purpose and then details response format, which is good. However, it could be tightened slightly without losing clarity.

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 having no output schema, the description comprehensively explains the response fields (tracked, expired, snapshot_dates) and their meanings. It also covers limits and data sources, making the tool's behavior fully understandable.

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?

The description adds meaning to both parameters: clarifies default and max for 'days', and explains 'window' as a snapshot family with examples. This goes beyond the schema's brief descriptions, providing practical guidance.

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 from daily snapshots, using a specific question ('how long has this edge existed and is it shrinking?') that distinguishes it from sibling tools like polymarket_edges, which likely give current edge values.

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 the tool's use case by contrasting a fresh edge with an old one, implying when to use it. It mentions limits (60-day TTL) but does not explicitly state when not to use it or name alternative tools.

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
Disambiguation4/5

Most tools have clearly distinct purposes (e.g., NPS park tools vs. Pipeworx queries vs. Polymarket analysis). Some overlap exists between ask_pipeworx and ask_pipeworx_grounded, and among the many Polymarket tools, but descriptions help differentiate them.

Naming Consistency3/5

Naming conventions vary: some use verb_noun (list_parks), others use descriptive phrases (ask_pipeworx_grounded, scan_competitor_ai_presence). While all use snake_case, there is no consistent pattern in prefixes or verb choice.

Tool Count2/5

35 tools is too many for a coherent server. The set appears to bundle multiple unrelated domains (NPS, Pipeworx, Polymarket, memory, subscriptions) into a single server, lacking focused scope.

Completeness3/5

Each domain has notable gaps (e.g., NPS lacks real-time conditions; Pipeworx lacks data ingestion tools; Polymarket lacks order placement). Some sub-areas (memory, subscriptions) are complete, but overall the surface is incomplete for the broad range of domains.

Resources