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Zenodo

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

A4.3/5.0
Behavior4/5

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

The description adds behavioral context beyond the annotations: it explains that decay numbers are from daily closes, not intraday, and that gaps in snapshots mean no scan occurred. It also details the response structure. Annotations already indicate readOnly and idempotent, and the description is consistent.

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 concise and well-structured: it starts with the main purpose, then details the response fields, and ends with limitations. Every sentence adds value without redundancy.

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?

Despite lacking an output schema, the description provides a thorough explanation of the response (tracked, expired, snapshot_dates) and covers limitations. It is complete for the tool's complexity.

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%, so baseline is 3. The description adds meaning by explaining 'days' as lookback (default 14, max 30) and 'window' as snapshot family with examples. It also clarifies the response structure, further aiding parameter 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 tool's purpose: providing edge persistence and decay telemetry from daily snapshots. It answers a specific question ('how long has this edge existed and is it shrinking?') and distinguishes itself from sibling tools like polymarket_edges by focusing on temporal analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when edge persistence history is needed, but does not explicitly state when to prefer this tool over alternatives or when not to use it. No sibling differentiation is provided, though the context of decay and persistence 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

A3.5/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, while ask_pipeworx, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all overlap in the 'how should I query data' space. Additionally, the tool set mixes two unrelated domains (Zenodo and Pipeworx) without any organizing principle, forcing agents to guess which family applies.

Naming Consistency2/5

All names are lowercase snake_case, but the semantic patterns are inconsistent: bare nouns for Zenodo tools (search, record, communities), product-prefixed names (pipeworx_*, polymarket_*), generic verbs (remember, forget, recall), and verb_noun compounds (list_subscriptions, generate_llms_txt). The server is named Zenodo, yet most tools carry a pipeworx or polymarket prefix, making the naming feel arbitrary relative to the server's identity.

Tool Count2/5

36 tools is excessive for a server whose stated identity is Zenodo; only 5 of the 36 tools actually relate to Zenodo, with the remaining 31 belonging to a separate Pipeworx data platform. This suggests a bundled or mislabeled server rather than a deliberately scoped tool surface, and even the Zenodo subset alone would be thin.

Completeness2/5

For the Zenodo domain implied by the server name, the surface is severely incomplete: it covers search and read/retrieval (search, record, record_files, communities, community_records) but entirely omits the deposit workflow that is central to Zenodo — no create, update, delete, versioning, or file upload/download tools. The unrelated Pipeworx side is over-built, but the actual Zenodo use case leaves agents with dead ends.

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