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Cfpb

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. Added
  2. Removed
  3. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, etc. The description substantially adds behavioral traits: it reads snapshots, returns a time-series for edge_pp_net, computes first_seen, trend, decay_pp_per_day, and limits (60-day TTL, daily closes not intraday). No contradiction with annotations; full transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose question, then systematically explains response fields and limits. Every sentence adds unique information without redundancy. Despite length, it earns its space through clear structure and useful detail.

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?

Given no output schema, the description thoroughly explains all return values (tracked[], expired[], snapshot_dates[]) with field meanings and examples (e.g., trend categories, decay computation). Limits and edge cases are covered. The description is complete for a tool with two simple parameters.

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

Parameters5/5

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

Schema coverage is 100%, so baseline is high. The description adds value beyond the schema: it provides default values (14 days, '1wk'), explains the meaning of each parameter (lookback, snapshot family), and adds context for window (e.g., '24hr | 1wk | 1mo'). This enriches understanding.

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 specific verb+resource: 'Edge persistence and decay telemetry' built from snapshots. It distinguishes itself from sibling tools like polymarket_edges by focusing on historical analysis and signal decay. The core question 'how long has this edge existed and is it shrinking?' precisely captures the tool's unique purpose.

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 this tool (when edge age and decay matter) but does not explicitly contrast with alternatives like polymarket_edges or polymarket_arbitrage. The phrase 'a fresh wide edge and a 3-week-old wide edge are different trades' provides strong usage context, but explicit 'use this when, use that when' guidance is missing.

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

A3.6/5.0
Disambiguation3/5

There are multiple overlapping tools for querying data (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim, bet_research) that could confuse an agent, though descriptions are detailed enough to distinguish most. Tools like polymarket_edges and polymarket_edge_tracker are closely related, and ai_visibility_check vs scan_competitor_ai_presence overlap.

Naming Consistency2/5

Naming is highly inconsistent: some follow verb_noun (cfpb_search_complaints, resolve_entity, subscribe, recall), but many use varied patterns like adjectives (ai_visibility_check), imperative phrases (ask_pipeworx, scan_competitor_ai_presence), or compound/specialized names (polymarket_arbitrage, generate_llms_txt). No consistent prefix or convention is used across the toolset.

Tool Count2/5

With 36 tools spanning diverse domains (prediction markets, SEC filings, CFPB complaints, AI visibility, npm packages, IPC subscriptions), the server is sprawling and over-scoped. Many tools are specialized niche additions (polymarket_fill_risk, scan_dependency, generate_llms_txt) that expand the count without strong cohesion.

Completeness3/5

The toolset covers core areas well (entity resolution, profile, comparison, recent changes, search, claims verification, subscriptions). However, gaps exist: no update/delete for CFPB complaints (read-only), no direct raw SEC filing retrieval, and some lifecycle operations (e.g., editing subscriptions) are missing.

Resources