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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

A4.4/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint, idempotentHint), description details response structure (tracked[], expired[], snapshot_dates[]) with field meanings, computational assumptions (daily closes of edge_pp_net, net default slippage, not intraday), and data gaps behavior. No contradictions 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?

Description is long but well-structured: starts with purpose, then explains response in three arrays with clear labels, and ends with limits. It is front-loaded with the core question. Slight verbosity in the middle but necessary for 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?

With no output schema and 2 well-documented parameters, the description provides a complete picture: what the tool returns (tracked, expired, snapshot_dates), field meanings, and limitations (60-day TTL, decay computation). No gaps remain for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with both parameters fully described in schema (defaults, ranges). Description adds no new semantic value beyond restating the schema's info (e.g., days lookback and window family). Baseline 3 is appropriate.

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?

Description clearly states it provides edge persistence and decay telemetry, answering a specific question: 'how long has this edge existed and is it shrinking?' It distinguishes from sibling tool polymarket_edges by focusing on time-series and decay, not just 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 when to use this tool versus alternatives (e.g., polymarket_edges for current edges) by focusing on history and decay. It provides limits like 60-day snapshot TTL, but doesn't explicitly list when-not-to-use or name alternatives directly.

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

A3.9/5.0
Disambiguation4/5

The tools are generally distinct, with clear purposes for NPI registry operations, but some overlap exists between ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded, which all route to the same underlying data but with different response modes. Additionally, bet_research and polymarket_edges both offer analysis of prediction markets, causing potential confusion.

Naming Consistency3/5

The naming is mixed: some tools follow a consistent verb_noun pattern (e.g., search, remember, forget), while others use descriptive but non-pattern names like ai_visibility_check or ask_pipeworx_grounded. There is also a mix of snake_case and camelCase (e.g., generate_llms_txt vs. ai_visibility_check).

Tool Count4/5

With 33 tools, the count is slightly high but still reasonable given the broad scope of the server, which covers NPI registry, company profiles, prediction markets, AI visibility, and more. Each tool serves a distinct purpose, though a few could potentially be consolidated.

Completeness3/5

The tool surface covers the NPI registry core (search, get by NPI) but lacks obvious CRUD operations like create, update, or delete for providers. For other domains like company profiles, it has good coverage, but the NPI-specific functionality feels incomplete without lifecycle management.