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Mitre Cwe

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

A4.3/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint, idempotentHint), the description adds critical behavioral details: snapshots are daily, decay computed from daily closes (not intraday), 60-day TTL for history, gaps mean no scan that day. No contradictions 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose with many details packed into a few sentences. While informative, it is not front-loaded and could be more concise. The response structure explanation is useful but adds length.

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 complexity of the tool, the description fully explains the response structure (tracked, expired, snapshot_dates) and limitations (60-day TTL, decay computation). No output schema exists, so the description adequately covers what the tool returns.

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% and both parameters are well-described in the schema. The description adds that days default is 14 and max is 30 (but omits the minimum clamp from schema), and repeats window defaults. This adds minimal value beyond the schema.

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 'how long has this edge existed and is it shrinking?' This specific purpose distinguishes it from sibling tools like polymarket_edges, which likely provides current edge data.

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 when to use (to assess edge freshness and decay) but does not explicitly state when not to use or mention alternatives. The guidance is clear but lacks explicit exclusions.

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

A3.6/5.0
Disambiguation2/5

Only 7 of 38 tools are specific to CWE (weakness, children, parents, etc.), while the rest are generic data query, prediction market, and utility tools. This creates massive overlap and confusion: an agent looking for CWE data will encounter many unrelated tools with similar generic names like ask_pipeworx, deep_research, etc.

Naming Consistency2/5

CWE-specific tools use a consistent noun pattern (weakness, children, parents, etc.), but the remaining tools mix snake_case, camelCase, and no clear pattern (e.g., ask_pipeworx, bet_research, generate_llms_txt). The overall naming is inconsistent.

Tool Count1/5

38 tools is far too many for a CWE server. The vast majority are unrelated to CWE, making the tool surface bloated and unfocused. A concise set of ~5-10 CWE-specific tools would be appropriate.

Completeness3/5

The CWE-specific tools (weakness, category, view, children, parents, descendants, relationship) cover the main use cases for querying the CWE database. However, the server also includes many unrelated tools that dilute its purpose, making it feel incomplete for someone strictly needing CWE data.

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