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Arcgis Kansas

by io.github.pipeworx-io

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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description reveals the tool reads from snapshots written on cache-miss, so gaps in snapshot_dates mean no scan occurred. It also discloses that decay is computed from daily closes of edge_pp_net (not intraday) and that history depth is bounded by a 60-day TTL. This goes well beyond the annotations, providing critical behavioral context.

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 dense but well-structured with clear sections (Args, RESPONSE, LIMITS). Every sentence carries useful information about response format, edge cases, and limitations. It's longer than average but justified by the tool's complexity.

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?

The response structure is fully described: tracked[] with time-series, trend, decay rate, expired[] with lifespan, and snapshot_dates[] with gap semantics. The description also explains the signed edge_pp_net (negative = SELL YES) and the median lifespan as a 'competition clock'. Given no output schema, this description compensates admirably.

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 schema already provides full descriptions for both days and window, so the base is covered (coverage 100%). The description adds the clamp ranges (2-30) and default values, but these are also in the schema. The window parameter is described as 'snapshot family' which adds a slight semantic nuance, but overall the description adds minimal extra value beyond the schema.

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 defines the tool as 'edge persistence and decay telemetry' built from daily snapshots, answering a specific temporal question about edge aging. It distinguishes itself from sibling tools like polymarket_edges by focusing on historical trend (persistence/decay) rather than current edge values. This provides a specific verb-resource pair and differentiates the tool.

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 clear use case: answering 'how long has this edge existed and is it shrinking?', and even explains the trading implication (fresh vs 3-week-old edges are different). It doesn't explicitly name alternative tools for when not to use it, but the context makes it clear this is for temporal analysis, not current edge discovery. The LIMITS section also warns about data gaps and TTL, which helps set expectations.

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
Disambiguation1/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all route questions; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker all deal with prediction market edges). The inclusion of memory tools (remember, recall, forget) alongside research tools further blurs boundaries.

Naming Consistency2/5

Naming conventions are mixed: some tools use snake_case (ai_visibility_check), some use underscores with prefixes (ask_pipeworx, polymarket_arbitrage), and others are more generic (query_layer, layer_info). There is no consistent pattern across the set.

Tool Count2/5

With 34 tools, the set is overly large for a geospatial server; most tools are unrelated to ArcGIS Kansas (e.g., prediction market tools, general research tools). Only 3 tools (search_datasets, layer_info, query_layer) are pertinent, making the count excessive and unfocused.

Completeness1/5

The server claims to be an ArcGIS Kansas tool but provides only basic layer querying and dataset search. Missing essential GIS operations such as editing, spatial analysis, or advanced queries, making it severely incomplete for its stated purpose.

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