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Data Norfolk

by io.github.pipeworx-io

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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Disclosures beyond annotations: OAuth requirement, delivery channel constraints (SMS cap, phone verification, webhook auto-disable). Idempotent annotation is present but not repeated; no contradiction. Could add more on idempotency behavior.

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?

Front-loaded with purpose and return value, then details. Dense but no fluff; slightly long but warranted for complexity. Could be more structured with bullet points.

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?

Highly complete given no output schema: covers all types, delivery options, prerequisites, and constraints. Missing only minor details like error handling or idempotency effects, but overall comprehensive.

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?

Schema coverage is 100%, but the description enriches each parameter with examples and constraints (e.g., sec_8k item codes, SMS cap, webhook signing). Adds significant value over schema alone.

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 creates a proactive monitoring subscription and returns a subscription ID. It distinguishes from siblings like list_subscriptions (listing) and unsubscribe (deleting) by focusing on creation.

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: requires Pipeworx OAuth account, lists supported types and delivery channels. Excludes anonymous/BYO users. However, it does not explicitly mention when not to use this or directly contrast with alternative tools.

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
Disambiguation1/5

ask_pipeworx and ask_pipeworx_beta are currently identical, deep_research overlaps ask_pipeworx for multi-faceted questions, and the five Polymarket tools plus bet_research all target the same market-analysis space. Several tools appear to do the same thing, and even detailed descriptions can't fully separate them.

Naming Consistency3/5

All names are lowercase snake_case and mostly readable, but the set mixes bare nouns (datasets, query, recall) with verb phrases (generate_llms_txt, validate_claim) and domain-prefixed compounds (polymarket_edges, pipeworx_trending). The ask_pipeworx family is internally consistent, but the overall pattern is not uniform.

Tool Count2/5

34 tools is well above the 25-tool threshold for a coherent set, especially since many are meta-tools (suggest_questions, discover_tools, pipeworx_feedback, pipeworx_trending) or one-off utilities (generate_llms_txt, scan_dependency). The server tries to cover data lookup, prediction markets, memory, subscriptions, and AI visibility in a single surface.

Completeness3/5

Within each subdomain (data lookup, memory, subscriptions, Polymarket) the main workflows are covered, and the memory/subscription clusters have full CRUD. But the server name promises Norfolk Open Data, which is barely represented by three read-only tools, and odd one-offs like generate_llms_txt and scan_dependency have no supporting ecosystem.

Resources