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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?

Annotations already declare read-only, open-world, idempotent, and non-destructive. The description adds significant context beyond these: snapshot TTL limits, cache-miss behavior causing gaps, signed edge_pp_net semantics, and decay computation methodology. This fully discloses behavioral traits and edge cases.

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 long but well-structured with labeled sections (Args, RESPONSE, LIMITS) and front-loaded with the core purpose. Every sentence carries useful information, though it could be slightly more compact without losing value.

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, the description fully explains the response structure (tracked, expired, snapshot_dates), including edge cases like data gaps and TTL. It also covers limitations and methodology, making it complete for an agent to invoke and interpret results correctly.

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% for both parameters. The description adds context about 'window' being a snapshot family and clarifies the meaning of the signed value, which helps the agent understand parameter semantics beyond the schema. While not strictly necessary, it enhances understanding.

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's function: tracking edge persistence and decay over time using daily snapshots. It answers a specific question ('how long has this edge existed and is it shrinking?') and differentiates itself from sibling tools like polymarket_edges by focusing on telemetry rather than edge computation.

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 the tool by contrasting fresh vs. old edges ('a fresh wide edge and a 3-week-old wide edge are different trades'), giving a clear use case. However, it does not explicitly name alternatives or state when not to use it, though the sibling context makes the differentiation clear.

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
Disambiguation3/5

Several tools serve overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, and suggest_questions all handle question-answering, with beta currently identical to the main router. The Polymarket family has six distinct but related tools, and descriptions are detailed enough to differentiate, but an agent could still misselect when the boundaries are subtle.

Naming Consistency3/5

All tool names use snake_case, but the pattern is mixed: some start with verbs (resolve_entity, validate_claim), while many are noun phrases (entity_profile, bet_research, polymarket_edges). This is readable but not a consistent verb_noun convention, and the repeated ask_pipeworx_* and polymarket_* prefixes add some structure.

Tool Count2/5

At 33 tools, the surface is heavy for an agent to navigate. While the server covers a broad data-research and prediction-market domain, the count exceeds what is typically manageable, and several tools (ask_pipeworx_beta, discover_tools) could be collapsed or merged without losing core capability.

Completeness4/5

The tool set covers the domain well: querying, grounded verification, entity profiles, comparisons, prediction-market analysis, subscriptions, memory, and onboarding. Minor gaps exist (e.g., no tool to fetch a full SEC filing body directly, relying on ask_pipeworx routing), but there are no obvious dead ends for the stated purposes.