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Openfema

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

A4.6/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context: snapshot TTL (60 days), decay computed from daily closes not intraday, and details about snapshot gaps. 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 structured with a question, response format, and limits. It is front-loaded with purpose. A bit verbose but every sentence adds value; could be slightly trimmed but effective.

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 no output schema, the description thoroughly explains return fields (tracked, expired, snapshot_dates) and their meanings. It also covers input constraints and limitations, making the tool fully understandable without additional references.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds defaults, max values, and meaning for 'window' (snapshot family), plus explains output structure, enhancing parameter understanding 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's purpose: 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots' and answers a specific question about edge longevity and shrinkage. It distinguishes from siblings like polymarket_edges by focusing on historical persistence rather than current edges.

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 contrasting fresh vs. old edges ('a fresh wide edge and a 3-week-old wide edge are different trades'). It implies but does not explicitly state alternatives or when not to use.

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

The tool set has several overlapping families: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, the discovery tools (list_datasets, discover_tools, suggest_questions) all serve a 'what can I do here' purpose, and ai_visibility_check is wrapped by scan_competitor_ai_presence. The polymarket_* tools are well-differentiated, but the heavy overlap in the meta-tools makes selection error-prone.

Naming Consistency2/5

Naming is a mix of conventions with no unifying pattern: family prefixes appear as ask_pipeworx_*, pipeworx_*, and polymarket_*, while unrelated tools use bare nouns (entity_profile, recent_changes), verb-first names (validate_claim, search_within), and inconsistent styles. The three actual FEMA tools (disaster_declarations, list_datasets, query_dataset) share no prefix that ties them to the server's stated name.

Tool Count2/5

34 tools exceeds the 'too many' threshold, and the count is unjustified by the server's apparent scope: only 3 of 34 tools relate to OpenFEMA data, with the remaining 31 being a grab-bag of Pipeworx routing, Polymarket betting, memory, subscription, and AI-visibility utilities. The bulk is either redundant with the meta-routers or off-domain for a server named 'Openfema'.

Completeness2/5

For FEMA specifically, list_datasets + query_dataset covers generic read-only access and disaster_declarations adds a convenience wrapper, but the domain is extremely thin and lacks FEMA-specific conveniences (e.g., geographic aggregation, multi-dataset joins, incident summaries). For the broader Pipeworx universe the routing coverage is actually decent, but that makes the FEMA-named server's surface feel incoherent — an agent expecting a FEMA toolset finds most of its value in unrelated prediction-market and brand-visibility tools.

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