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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 readOnly, idempotent, and non-destructive behavior. The description adds substantial context: history depth bounded by a 60-day TTL, snapshots written on cache-miss, gaps mean no scan, decay computed from daily closes net of slippage (not intraday), and the response includes expired opportunities with lifespan. This goes far beyond annotation hints and fully explains behavioral quirks.

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: purpose, args, RESPONSE, LIMITS. It is front-loaded with the core purpose. While somewhat verbose, every sentence conveys necessary information, especially given the absence of an output schema. It earns its length but could be tightened slightly.

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?

Without an output schema, the description thoroughly explains the response structure (tracked[], expired[], snapshot_dates[]), field meanings, and interpretation (median lifespan as competition clock). It also covers historical limitations and data gap behavior. The tool is moderately complex and this description fully equips an agent to use it 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?

The input schema descriptions cover both parameters 100% (days and window, with defaults and allowed values). The description repeats the defaults and adds minor framing ('snapshot family') but does not provide new meaning beyond the schema. Baseline of 3 is appropriate because the schema carries the full weight.

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 states a specific purpose: 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots.' It answers a clear question ('how long has this edge existed and is it shrinking?') and distinguishes itself from sibling tools like polymarket_edges by focusing on historical persistence and decay rather than 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 clearly implies when to use this tool: when you need to assess the age and trend of an edge, noting that 'a fresh wide edge and a 3-week-old wide edge are different trades.' It does not explicitly name alternatives, but the context differentiates it from current-edge tools. It lacks explicit exclusions but the intended use case is 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

A3.5/5.0
Disambiguation2/5

Many tools overlap in purpose: ask_pipeworx and ask_pipeworx_beta are identical, while ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve as query/entry-point tools. The two tax-specific tools are distinct, but the sheer number of generic data-access tools makes it difficult for an agent to select the right one.

Naming Consistency2/5

Naming is a mix of snake_case (ask_pipeworx, tax_search), camelCase (ask_pipeworx_beta, compare_entities, discover_tools), and inconsistent verb styles (resolve_entity vs entity_profile vs scan_competitor_ai_presence). No clear pattern is discernible.

Tool Count1/5

The server is named 'Tax Regulations' but only 2 of 33 tools are tax-related. The other 31 tools are unrelated Pipeworx data-access, memory, subscription, and Polymarket tools, making the count wildly excessive and mismatched with the apparent purpose.

Completeness3/5

For the tax regulation domain, tax_search and tax_regulation cover keyword discovery and full-text retrieval, which is a functional core. However, the set lacks any other tax-specific operations (e.g., updates, comparisons, planning), and the majority of the tool surface is irrelevant to the stated server purpose, leaving notable gaps for an agent expecting a coherent tax toolset.