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Hex Pm

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds substantial context beyond these: snapshot data gaps, TTL limits, computation on daily closes, and the full response structure. There is no contradiction with annotations.

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 dense but every sentence earns its place. Purpose is front-loaded, followed by clear sections for arguments, response structure, and limits. It is well-organized and contains no filler.

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?

Even without an output schema, the description thoroughly documents the response fields (tracked[], expired[], snapshot_dates[]), their semantics, and edge cases (gaps, TTL). It covers calculation details and practical implications, making it fully usable by an agent.

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%: both parameters (days with default/clamp, window with allowed values) are fully described. The description repeats defaults and calls window a 'snapshot family' but adds no new meaning beyond the schema. Baseline 3 is appropriate when the schema carries full descriptive weight.

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?

Purpose is unambiguous: the first sentence states it provides 'edge persistence and decay telemetry built from daily polymarket_edges snapshots' and the description answers a specific analytical question. It clearly distinguishes from sibling tools like polymarket_edges by focusing on historical time-series rather than current edge values.

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?

Provides clear context for when to use the tool: to understand edge persistence and decay, with a concrete example. It also documents history limits (60-day TTL) and data gaps. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of full exclusion guidance.

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

A3.8/5.0
Disambiguation2/5

Several tools occupy overlapping question-answering territory: ask_pipeworx_beta currently behaves identically to ask_pipeworx, while ask_pipeworx_grounded, deep_research, and validate_claim all route the same data catalog and differ mainly in output guarantees. The six Polymarket tools also split edge detection, arbitrage, and fill-risk in ways that are easy for an agent to conflate. Clear exceptions like the memory and subscription trios keep it from a 1.

Naming Consistency4/5

Names are uniformly lowercase snake_case and most follow a readable verb-first or domain-prefixed pattern (get_package, list_releases, scan_dependency, ask_pipeworx_*). The Polymarket family uses noun phrases after a prefix (polymarket_edges, polymarket_fill_risk) and a few names are noun-first (entity_profile, recent_changes), which is a minor inconsistency rather than chaos.

Tool Count2/5

35 tools is well beyond the comfortable 3-15 range and even above the 16-25 heavy range. The broad Pipeworx data scope justifies some expansion, but identical ask_pipeworx_beta, six overlapping Polymarket tools, and unrelated utility families (Hex.pm, AI visibility, memory, llms.txt) suggest bloat rather than deliberate scoping.

Completeness4/5

Within its main data-access purpose, the surface is unusually complete: query (ask_pipeworx), grounded verification (ask_pipeworx_grounded/validate_claim), deep research, entity resolution/profiling, comparison, change feeds, and search-within are all present, and memory/subscription subdomains have full CRUD. There are minor gaps for the package side (no docs/dependents) and the hodgepodge of domains makes a single 'complete' surface hard to define, but no workflow hits a hard dead end.

Resources