Skip to main content
Glama

Arcgis Chapelhill

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?

The description adds substantial behavioral context beyond the annotations, including the 60-day snapshot TTL, snapshot behavior on cache-miss with gaps, decay computed from daily closes rather than intraday, and the signed nature of edge_pp_net (negative = SELL YES). This is far more than the readOnly/openWorld/idempotent hints already provide.

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 ARGS, RESPONSE, and LIMITS sections, and it front-loads the core purpose. However, it is fairly long and includes some redundancy with the schema (e.g., repeating default values), so it does not earn a perfect 5.

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?

Without an output schema, the description fully compensates by explaining the response structure (tracked[], expired[], snapshot_dates[]) with sufficient detail, and also covers important edge cases (snapshot gaps, TTL bounds, data freshness). This makes the tool usable without needing to infer return behavior.

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 description coverage is 100%, so the baseline is 3. The description repeats the defaults and adds slight context (e.g., 'lookback', 'snapshot family'), but it does not substantially enrich the parameter meanings beyond what is already in the schema. It even omits the enum values for window that the schema includes.

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 function: 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots' and answers a specific question: 'how long has this edge existed and is it shrinking?' This is a specific verb+resource+scope that distinguishes it from the sibling tool polymarket_edges, which likely shows 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 implies when to use the tool: when you need to know edge persistence and decay, and even provides a concrete use case ('the median lifespan is your competition clock'). However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Arcgis Chapelhill toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx and ask_pipeworx_beta are currently literally identical, and the polymarket_* family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread, polymarket_edge_tracker) all orbit the same prediction-market opportunity space. The descriptions are detailed and do help, but the sheer number of near-synonymous entry points makes misselection likely.

Naming Consistency4/5

The vast majority of tools follow a consistent snake_case, verb-first pattern: ask_pipeworx, compare_entities, query_layer, resolve_entity, search_datasets, validate_claim. Minor deviations exist — the polymarket_* tools are noun-phrase style and a few names like entity_profile, layer_info, and ai_visibility_check are noun-led — but the overall style is uniform enough to be predictable.

Tool Count2/5

34 tools is already in the overstuffed range, but the bigger problem is that only 3 of them (search_datasets, layer_info, query_layer) relate to the server's stated ArcGIS/Chapel Hill identity. The other 31 tools appear to be an unrelated Pipeworx data-research, prediction-market, memory, and subscription bundle merged into this server, making the count grossly disproportionate to the apparent purpose.

Completeness2/5

The three GIS tools form a usable read-only search → schema → query workflow, so the ArcGIS domain is not completely absent. However, as a whole the server has no coherent domain to be complete for, and the ArcGIS side lacks broader capabilities like layer enumeration, spatial filters/statistics, or any write/edit operations. For a server named Arcgis Chapelhill, having 31 out-of-scope tools constitutes a major completeness failure.

Resources