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Stocktwits

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).

TDQS

A4.7/5.0
Behavior5/5

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

The description goes beyond annotations by detailing limitations (60-day TTL, dependency on snapshot runs), explainations of data gaps, and how decay numbers are computed (daily closes, not intraday). This adds significant behavioral transparency that annotations alone (readOnlyHint, idempotentHint) do not cover.

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 well-structured with separate sections for arguments, response, and limits, making it easy to parse. However, it is somewhat verbose; it could be slightly more concise without losing essential details.

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 the lack of an output schema, the description comprehensively explains the response structure (tracked, expired, snapshot_dates) with clear definitions of each field. It covers all necessary context for a tool with two optional parameters and no nested objects.

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?

The description adds meaning to the parameters by specifying defaults (days=14, window='1wk'), valid ranges (days max 30), and the role of window as a snapshot family. This complements the 100% schema coverage effectively.

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 explicitly states the tool provides 'edge persistence and decay telemetry' from daily snapshots, addressing the question of how long an edge has existed and if it's shrinking. It clearly differentiates from sibling tools like polymarket_edges and polymarket_arbitrage by focusing on historical edge behavior.

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 context on when to use the tool by explaining that a fresh wide edge differs from an old one, implying it should be used for assessing edge longevity. However, it does not explicitly state when not to use it or compare directly with siblings, though the context 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 serve overlapping functions: three ask_pipeworx variants, two deep research tools, and multiple polymarket tools. StockTwits-specific tools are distinct but the overall set has significant ambiguity between Pipeworx and Polymarket tools.

Naming Consistency2/5

Naming styles are mixed: some use lowercase (ask_pipeworx), some use underscores (ai_visibility_check), and some use prefixes (pipeworx_feedback, polymarket_arbitrage). No consistent pattern across the tool set.

Tool Count3/5

40 tools is on the higher end but not extreme. However, many tools belong to the Pipeworx ecosystem, which seems separate from StockTwits, making the set feel bloated and unfocused for a single server.

Completeness2/5

StockTwits social features are adequately covered (symbol search, streams, trending), but the inclusion of Pipeworx tools creates a sprawling surface without complete coverage in any one domain. Missing core StockTwits features like user profiles or direct messaging.

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