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Neso

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. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint) are fully supported. The description adds rich behavioral context: output structure (tracked[], expired[], snapshot_dates[]), decay calculation details (computed on absolute value, negative for SELL YES), and limitations (60-day snapshot TTL, no intraday data). No contradictions.

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 information-dense but front-loads the core purpose. Every sentence adds value, though it could be slightly more concise. The structure is logical: purpose, output explanation, limitations.

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 two simple parameters, no output schema, and supportive annotations, the description fully explains what the tool returns (tracked, expired, snapshot_dates) and its limitations (TTL, not intraday). It is comprehensive for the tool's complexity.

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 description coverage is 100% with both parameters described. The description adds default values and clamp range for 'days', which is helpful but not essential. It explains the meaning of 'window' as snapshot family. Baseline 3 is appropriate since the schema already does heavy lifting.

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: 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots.' It answers specific questions about edge duration and decay, distinguishing it from the sibling tool 'polymarket_edges' which likely provides current edge 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 analyzing how long edges have existed and their decay trend, with examples like 'a fresh wide edge and a 3-week-old wide edge are different trades.' However, it does not explicitly state when to use this tool versus alternatives or provide exclusion criteria.

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

A3.9/5.0
Disambiguation2/5

The ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded trio is genuinely confusing — beta is explicitly identical to stable, and grounded differs only in output format, so agents will struggle to pick the right one. The six Polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread, bet_research) also blur together despite distinct purposes, and ai_visibility_check vs scan_competitor_ai_presence overlap heavily.

Naming Consistency4/5

Naming is largely consistent: snake_case throughout, with a strong verb-first pattern (list_subscriptions, resolve_entity, validate_claim, compare_entities, discover_tools) and clear domain prefixes for clusters (neso_, pipeworx_, polymarket_). The only inconsistency is the ask_pipeworx family, which differentiates by bare suffix (_beta, _grounded) rather than a descriptive verb.

Tool Count3/5

35 tools is on the heavy side, but the server is a broad multi-domain data platform (SEC, FDA, FRED, NESO, Polymarket, npm, memory, subscriptions, discovery) where the count is arguably justified. Several tools could be consolidated — the three ask_pipeworx variants are redundant, and scan_competitor_ai_presence largely wraps ai_visibility_check — which would tighten the surface meaningfully.

Completeness4/5

Coverage is strong across the stated domains: lookups, deep research, entity resolution, claim verification, comparisons, memory lifecycle (remember/recall/forget), subscription lifecycle (subscribe/unsubscribe/list/recent_alerts), discovery (discover_tools, suggest_questions), feedback, and trending. Minor gaps exist (no direct document-fetch tool, scan_dependency is npm-only in v1) but nothing that creates a dead end.

Resources