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Adsb

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

A4.5/5.0
Behavior5/5

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

The description adds substantial behavioral context beyond annotations: it explains the time-series computation, trend classification, decay calculation, expired opportunities, snapshot gaps, and limits (60-day TTL, daily closes). This fully informs the agent of read-only, idempotent behavior.

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

Conciseness3/5

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

The description is detailed but somewhat verbose, with all-caps section labels and redundant phrasing. It could be more concise while retaining essential information.

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 fully compensates by detailing the response fields (tracked, expired, snapshot_dates) and their semantics. It also covers limits and data granularity, making the tool's behavior completely understandable.

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?

With 100% schema coverage, baseline is 3. The description adds value by providing defaults, clamps, and response structure details not in the schema, such as the format of tracked, expired, and snapshot_dates arrays.

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 tracks edge persistence and decay from daily snapshots, answering a specific question about edge age and shrinkage. It distinguishes from sibling tools like polymarket_edges by focusing on historical time-series rather than 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 provides clear context on when to use the tool (e.g., to differentiate a fresh wide edge from an old one) and explains arguments and limits. However, it does not explicitly state when not to use it or provide alternative tool names.

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
Disambiguation2/5

Several clusters of tools have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, validate_claim, and bet_research all overlap as query/research entry points, and ai_visibility_check vs. scan_competitor_ai_presence plus the six polymarket_* tools create further confusion. An agent would often need deep description reading to pick the right tool.

Naming Consistency2/5

Naming mixes consistent verb_noun forms (get_aircraft, resolve_entity, validate_claim) with noun phrases (aircraft_near, military_aircraft, recent_alerts), adjective-led names (polymarket_arbitrage), and conversational names (ask_pipeworx, suggest_questions). Subgroups like polymarket_* are internally consistent, but overall there is no unified pattern.

Tool Count2/5

35 tools is high for any cohesive server, especially one named 'Adsb' where only 4 tools relate to aircraft tracking. The count is inflated by many overlapping meta-research, prediction-market, memory, and subscription tools, making it feel like several servers were merged into one.

Completeness2/5

For the implied 'Adsb' domain, only live ADSB positioning is covered; airport info, flight schedules, route search, and aviation weather are missing. Even as a general data/betting server, there are gaps like a direct stock-quote tool and unclear lifecycle coverage across the mixed feature set, so agents will likely hit dead ends.

Resources