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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. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint true and destructiveHint false. The description adds rich behavioral context beyond these: details on snapshot gaps (cache miss), response fields (tracked, expired, snapshot_dates), computation of decay_pp_per_day, and that decay numbers come from daily closes not intraday. 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 a clear core question, parameter definitions, response breakdown, and LIMITS section. It is concise for the amount of detail provided, though it could be slightly tighter by removing parenthetical asides or redundant phrasing. Overall, every sentence serves a purpose.

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 explains the entire response structure with fields like tracked (with subfields first_seen, trend, decay_pp_per_day), expired (with lifespan_days), and snapshot_dates. It also covers limitations (TTL, snapshot start). For a tool with only two optional parameters, this is exceptionally complete.

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?

Input schema already documents both parameters (days, window) with descriptions, defaults, and ranges. The description restates these values (default 14, max 30; default '1wk') but does not add significant new semantics beyond what the schema provides. With 100% schema coverage, the baseline is 3.

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 purpose: 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots.' It answers the specific question 'how long has this edge existed and is it shrinking?', and distinguishes itself from sibling tools like polymarket_edges by focusing on historical time-series rather than 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 provides a rationale for when to use: comparing a fresh wide edge versus an old wide edge ('the latter is wide for a reason nobody is willing to take'). It also includes LIMITS detailing constraints like the 60-day snapshot TTL and dependency on snapshotting being enabled. However, it does not explicitly exclude alternative tools or provide comprehensive when-not-to-use guidance.

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 toolset is overwhelmingly fragmented: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical entry points; polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk heavily overlap; and ai_visibility_check vs scan_competitor_ai_presence cover the same task. The five actual Wiktionary tools are distinct but are lost among dozens of unrelated research and prediction-market tools, making selection highly ambiguous.

Naming Consistency3/5

All names use snake_case and several logical prefixes (ask_pipeworx, polymarket_, pipeworx_) create local patterns. However, the naming mixes noun-style commands (definition, etymology, pronunciations, summary) with verb-style commands (search, remember, forget, validate_claim), and no consistent verb_noun convention carries across the whole set.

Tool Count1/5

36 tools is already heavy, but the deeper problem is that only 5 tools actually belong to a Wiktionary server while 31 tools serve unrelated Pipeworx, Polymarket, memory, and marketing-audit functions. The count is wildly inappropriate for the declared server purpose.

Completeness2/5

The Wiktionary-relevant tools cover basic word lookup—search, summary, definition, etymology, pronunciations—but omit common dictionary operations like translations, usage examples, inflected forms, or random entries. The non-Wiktionary majority does not fill these gaps; it just makes the surface area incoherent and hard to reason about.