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Arcgis Sanjose

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).

TDQS

A4.4/5.0
Behavior5/5

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

Annotations indicate read-only, idempotent, non-destructive. The description adds key behavioral context: history bounded by 60-day snapshot TTL, decay computed from daily closes not intraday, and gaps in snapshots due to cache-misses. 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 thorough and front-loaded with purpose, but its length is justified by the complexity of the response structure and limitations. Could be slightly more concise, but well-organized.

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?

Despite no output schema, the description details the response fields (tracked[], expired[], snapshot_dates[]) and explains limitations. Complete for a tool with 2 parameters and complex output.

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 coverage is 100% with descriptions for both parameters. The description adds default values and constraints (e.g., 'days, default 14, max 30') but does not provide significant extra meaning beyond the schema. Baseline 3 is appropriate.

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' and answers 'how long has this edge existed and is it shrinking?'. It distinguishes itself from siblings like polymarket_edges by focusing on historical time-series and decay analysis.

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 gives context on when to use the tool (e.g., differentiating fresh vs. old edges) but does not explicitly state when not to use or list alternatives. The usage is implied through the telemetry focus.

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
Disambiguation3/5

While many tools have distinct purposes, there is overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as multiple Polymarket and entity-related tools. Descriptions are detailed but could confuse agents on which tool to use for a specific query.

Naming Consistency3/5

Most tool names use snake_case and many start with verbs, but there is inconsistency with noun-starting names like entity_profile, layer_info, and pipeworx_feedback. No strong verb_noun or other consistent pattern across the set.

Tool Count3/5

With 33 tools, the count is relatively high but could be justified for a broad data platform. However, given the server name 'Arcgis Sanjose', the number seems excessive as most tools are unrelated to ArcGIS geospatial functions.

Completeness2/5

The tool set is severely incomplete for the implied ArcGIS San Jose domain, with only 3 tools (search_datasets, layer_info, query_layer) supporting that purpose. The rest are from the Pipeworx ecosystem, creating a mismatch between server name and actual functionality.

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