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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

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds rich behavioral context: response structure (tracked, expired, snapshot_dates), how decay is computed (daily close, not intraday), and limitations (60-day TTL, snapshot gaps). No contradictions.

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 well-structured with clear sections (response fields, limits) but could be slightly more concise. It front-loads the purpose effectively. Minor redundancy in explaining tracked and expired fields.

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?

Given no output schema, the description fully explains all response fields (tracked, expired, snapshot_dates) with details on edge_pp_net time-series, trend, decay, lifespan, and limitations. Covers everything needed for an agent to understand and invoke the tool.

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?

Input schema has 100% coverage with clear descriptions for both parameters (days, window). Description adds extra context like default values and clamp, but doesn't significantly expand beyond the schema. Baseline 3; small addition justifies 4.

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, answering a specific question about edge age and shrinkage. It distinguishes itself from sibling polymarket_edges (which likely returns current edges) by focusing on historical tracking.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly explains when to use – to differentiate between a fresh wide edge and an old one that may not be profitable. It implies alternatives like polymarket_edges for current edges without historical context, and notes limitations (TTL, snapshot gaps).

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

A3.8/5.0
Disambiguation2/5

Several tools blur together: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer factual questions with overlapping routing behavior, while polymarket_edges, polymarket_arbitrage, and bet_research all surface prediction-market opportunities. Long descriptions help, but the boundaries between these clusters are genuinely unclear, and the three IEEE tools are buried in a sea of unrelated Pipeworx tools.

Naming Consistency4/5

The naming is predominantly snake_case with clear family prefixes like ieee_, ask_pipeworx_, and polymarket_, and most tools follow a readable verb_noun or noun_verb shape. Minor deviations exist (remember/recall/forget, bet_research, pipeworx_trending) but there is no camelCase/mixed-convention problem, so the overall pattern is predictable.

Tool Count1/5

A server named 'Ieee Standards' exposes 34 tools, yet only three of them (ieee_search, ieee_standard_search, ieee_article) actually serve that domain. The remaining 31 tools form a general Pipeworx data, prediction-market, memory, and subscription platform, which is an extreme scope mismatch for the stated server purpose.

Completeness4/5

For the IEEE lookup domain, the three IEEE tools cover the core read-only workflow: broad corpus search, standards-specific search, and full metadata retrieval by article number or DOI. Minor gaps exist (browsing by committee, revision/status history, full-text access) but those are workable or inherently restricted by IEEE's paywall.