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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

A4.4/5.0
Behavior5/5

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

The description goes beyond the annotations (readOnlyHint, openWorldHint, idempotentHint) by explaining data availability (cache-miss snapshots, 60-day TTL), the computation basis (daily closes, not intraday), and the meaning of gaps in snapshot_dates. This is rich behavioral context that helps the agent understand limitations and interpret results.

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 long but well-structured with clear sections (intro, args, response, limits). It is front-loaded with the core purpose. Each sentence adds useful information, though some phrasing like 'the latter is wide for a reason nobody is willing to take' is slightly editorial. Overall, it earns its place with minimal waste.

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?

With no output schema, the description thoroughly explains the response structure (tracked[], expired[], snapshot_dates[]) and their semantics. It also covers edge cases like missing snapshot gaps, TTL limits, and computation details. This is a complete picture for a moderately complex tool.

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 coverage is 100%, so the baseline is 3. The description repeats the parameter defaults ('days (lookback, default 14, max 30)', 'window ... default 1wk') which are already in the schema, and does not add additional semantic meaning beyond what the schema descriptions provide. Thus it meets but does not exceed the baseline.

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 provides 'edge persistence and decay telemetry' from daily snapshots, answering a specific question about edge age and decay. This distinguishes it from siblings like polymarket_edges (which likely lists current edges) and polymarket_arbitrage (which likely detects arbitrage opportunities).

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 explains when this tool is valuable: 'a fresh wide edge and a 3-week-old wide edge are different trades' and mentions the median lifespan as a 'competition clock'. It does not explicitly name alternative tools, but the context and sibling list make the differentiation clear. It lacks explicit exclusions but provides strong usage context.

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

B3.2/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical in function, while compare_entities and entity_profile both fan out across data sources. The PLOS-specific tools (article, search, recent) are distinct, but the broader set creates confusion about which entry point to use for general data questions.

Naming Consistency2/5

The naming is a mix of single-word nouns (article, recent), verb phrases (search_authored_by, validate_claim), and adjective_noun constructions (recent_changes, recent_alerts). While most multi-word names use snake_case, the lack of a consistent prefix or verb_pattern (e.g., some start with action verbs, others with data categories like polymarket_ or pipeworx_) makes the set feel inconsistent.

Tool Count2/5

At 35 tools, the server is heavily over-scoped for a PLOS journal interface—only 4 tools (article, search, search_authored_by, recent) actually relate to PLOS. The remaining 31 tools form a broad Pipeworx/Polymarket data platform, which suggests the server is trying to do far more than its name implies.

Completeness2/5

For the stated domain (PLOS), the surface is thin: basic search, fetch, recent, and author search lack advanced features like citation metrics, journal browsing, or full-text download links. Conversely, the Pipeworx tools are extensive but unrelated to PLOS, so the set is simultaneously over-complete in unrelated areas and incomplete for its apparent purpose.

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