Skip to main content
Glama

Arcgis Tigard

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 already provide readOnlyHint, idempotentHint, etc. The description adds important behavioral details: data comes from daily snapshots, history limited by 60-day TTL, decay computed from daily closes, and snapshot gaps meaning no scan.

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 and front-loaded with the core purpose. It is slightly lengthy but every sentence adds value given 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?

With no output schema, the description fully documents the return structure (tracked[], expired[], snapshot_dates[]) and key fields, making it complete for an agent.

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 clear descriptions for both parameters. The description rephrases but does not significantly add new semantic meaning beyond what the schema provides.

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 it provides 'edge persistence and decay telemetry' and answers a specific question. It distinguishes itself from the sibling 'polymarket_edges' by being a higher-level analysis built on snapshots.

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 usage for understanding edge persistence and decay, but does not explicitly state when not to use or name alternatives. However, the context with sibling tools makes it clear.

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

All Arcgis Tigard 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

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the various ask_pipeworx variants and entity research tools (entity_profile, compare_entities, recent_changes). The subtle differences between ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are likely to cause agent misselection.

Naming Consistency2/5

Tool names use inconsistent patterns: snake_case (ask_pipeworx, query_layer) mixed with descriptive phrases (ai_visibility_check, generate_llms_txt) and no clear verb_noun structure. Some names are vague (process, run) though those are absent here; overall naming is arbitrary.

Tool Count2/5

34 tools is too many for an Arcgis Tigard server. The majority are generic Pipeworx data query tools (27+ tools) that have little to do with ArcGIS, making the tool count feel bloated and unfocused for the server's stated purpose.

Completeness1/5

The server severely lacks ArcGIS-specific functionality. Only three tools (search_datasets, query_layer, layer_info) are relevant to ArcGIS; the rest are unrelated Pipeworx tools. Essential ArcGIS operations like editing, analysis, or visualization are missing, making the surface incomplete.

Resources