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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).

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior; the description adds substantial non-obvious context beyond them: 60-day snapshot TTL, snapshot gaps due to cache-miss scanning, decay computed from daily closes (not intraday), and a detailed explanation of expired[] vs tracked[]. This far exceeds the baseline and enriches the agent's understanding of 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 explicit RESPONSE and LIMITS sections, making it scannable. Every sentence contributes semantically (field meanings, TTL, gap causes). It earns a 4 rather than 5 because it could be tightened without losing critical detail, but it is far from bloated.

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 specifies return shapes: tracked[] with fields (edge_pp_net timeseries, first_seen, trend, decay_pp_per_day), expired[] with lifespan_days, and snapshot_dates[] with gap explanation. It also covers data limitations (TTL, snapshot start time) and computation basis. This is a complete and self-sufficient explanation for the agent.

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 already documents both parameters with descriptions, including defaults and allowed values, so baseline is 3. The description repeats the defaults and adds only the phrase 'snapshot family' to frame window, but this is already in the schema. There is also a minor inconsistency: description says max 30 for days, while schema says clamp 2-30, which is a slight loss of precision.

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?

Uses a specific verb (tracker) and resource (polymarket edge snapshots) while clearly stating it measures edge persistence and decay. The phrase 'how long has this edge existed and is it shrinking?' crisply defines the tool's purpose and implicitly differentiates it from sibling polymarket_edges, which likely shows 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?

Provides clear context: use when evaluating edge age/trend, and illustrates the difference between fresh vs. old edges ('a 3-week-old wide edge is wide for a reason nobody is willing to take'). However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of full disambiguation.

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
Disambiguation1/5

The tool set includes multiple pairs of nearly identical tools (e.g., ask_pipeworx and ask_pipeworx_grounded, bet_research and polymarket_arbitrage) that overlap heavily in purpose. Many tools also combine unrelated functions, making it difficult for an agent to select the right one without confusion.

Naming Consistency1/5

Tool names follow no discernible pattern: snake_case (ai_visibility_check), verb_noun (ask_pipeworx, get_bill), and even lengthy descriptive names (scan_competitor_ai_presence) are mixed. The naming style is chaotic and inconsistent across the set.

Tool Count2/5

With 30 tools, the count is excessive for a server supposedly focused on OpenStates (state legislatures). Only a few tools (search_bills, get_bill, etc.) relate to the server's name, while the rest are tangentially related to data lookups, betting, or AI visibility, making the set bloated.

Completeness1/5

The server's core domain (state legislative data) is severely underserved: only about 5 tools cover bills and legislators, lacking basic CRUD operations like create, update, or delete. Many obvious operations (e.g., searching bills by subject, tracking votes) are missing, while unrelated tools dominate.