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Country State City

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

A4.5/5.0
Behavior5/5

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

Annotations already mark the tool as read-only and idempotent. The description goes beyond by detailing the response structure (tracked, expired, snapshot_dates), explaining how decay_pp_per_day is computed, and noting that snapshots are written on cache-miss. It also clarifies that decay numbers are from daily closes, not intraday.

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 sections for purpose, response breakdown, and limits. It is concise yet thorough, though slightly lengthy. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description thoroughly explains the response format (tracked array with fields, expired array with lifespan, snapshot dates). It covers the key elements needed for agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%. The description adds defaults for days (14, max 30, clamp 2-30) and window (default '1wk', options '24hr', '1mo'), which is valuable beyond the schema descriptions.

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 purpose: tracking edge persistence and decay over time from daily snapshots. It distinguishes itself from sibling tools like polymarket_edges by focusing on historical trends and decay metrics.

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 it (e.g., assessing edge age and decay) and provides limits (60-day TTL, snapshot gaps). It does not explicitly state when not to use it or name alternatives, but the context is clear.

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

A3.7/5.0
Disambiguation2/5

Several tools overlap enough to cause misselection: ask_pipeworx and ask_pipeworx_beta are functionally identical right now, ask_pipeworx_grounded and validate_claim both handle factual lookup/verification, and ai_visibility_check/scan_competitor_ai_presence are near duplicates in scope. The country/state/city tools are distinct but sit in a pile of unrelated Pipeworx tools, adding confusion.

Naming Consistency3/5

All names are lower_snake_case and families like polymarket_* and ask_pipeworx* help group tools, but the verb_noun convention is inconsistent: entity_profile, deep_research, recent_alerts, and pipeworx_trending are noun phrases, while remember/forget/subscribe are bare verbs. It is readable but not a predictable pattern.

Tool Count2/5

34 tools is above the practical ceiling for a focused MCP server, and the mismatch is severe: only 3 tools match the 'Country State City' name while 31 belong to a broad Pipeworx platform. A geographic server would need roughly 3-6 focused tools; this surface is bloted.

Completeness2/5

For the stated Country State City domain, list_countries/get_states/get_cities provide the basic hierarchy, but there is no city search, country/state detail lookup, or attribute discovery beyond the three list endpoints, making the useful geographic surface thin. For the Pipeworx domain the coverage is broader, but that confirms the identity mismatch and obscures the server's actual purpose.

Resources