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Arcgis Delawareco

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?

The description adds substantial behavioral context beyond the readOnly/idempotent annotations: it details response structure (tracked/expired/snapshot_dates), explains snapshot-gap semantics, TTL limits, and that decay is computed from daily closes. This is rich, non-obvious information that materially affects interpretation.

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 with clear sections (Args, RESPONSE, LIMITS) and is front-loaded with the purpose. Every sentence adds functional value, though the 'nobody is willing to take' phrase is illustrative rather than strictly necessary.

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?

With no output schema, the description carries full responsibility for explaining return values and constraints—it does so thoroughly, covering every field in tracked/expired/snapshot_dates, trend semantics, decay calculation, and data availability boundaries. This is complete for the tool's complexity.

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% for both parameters, and the description essentially repeats the schema's definitions (defaults, window values). It adds no new semantic detail beyond what the schema already provides, so the baseline 3 applies.

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 verb+resource ('Edge persistence and decay telemetry') and immediately distinguishes from siblings by focusing on historical persistence rather than listing current edges. It even explains the core question it answers ('how long has this edge existed and is it shrinking?').

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?

It clearly implies when to use the tool—when edge age/decay matters—by contrasting fresh vs. old edges. However, it does not explicitly name alternative tools or state when not to use it, leaving sibling differentiation implicit rather than direct.

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 have overlapping or redundant purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical in routing, and several polymarket tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) all surface trading opportunities with similar outputs. The three ArcGIS tools are distinct but buried among dozens of unrelated data/meta tools, making selection confusing.

Naming Consistency3/5

All names use snake_case, which is consistent, but the verb/noun pattern is inconsistent. Some are verb_noun (query_layer, resolve_entity), some are noun phrases (entity_profile, polymarket_edges, recent_alerts), and some are bare verbs (recall, remember, forget, subscribe). The naming style is readable but not predictably patterned.

Tool Count1/5

34 tools is already high, but the severe issue is that only 3 of them (search_datasets, query_layer, layer_info) relate to the server's stated ArcGIS Delaware County purpose. The other 31 are Pipeworx data, memory, subscription, and prediction-market tools, which is a blatant scope mismatch. The tool count is not appropriate for the advertised server domain.

Completeness1/5

For an ArcGIS Delaware County GIS server, the surface is extremely thin: only search, query, and layer metadata exist. There are no tools for editing features, uploading data, managing layers, or exporting maps. Conversely, the Pipeworx tools form a broad but fragmented domain with many monitoring and meta-tools but no clear end-to-end workflow. The set is severely incomplete for its apparent dual purpose.

Resources