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Peopledatalabs

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

A4.8/5.0
Behavior5/5

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

Discloses key behaviors beyond annotations: returns subscription id, requires OAuth, SMS 10/day cap, webhook auto-disable after 10 failures, one-time webhook signing secret, and always-on feed. These are important operational implications that the annotations alone (readOnlyHint=false, openWorldHint=true) do not convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

Dense but well-factored: front-loaded with purpose and return, then organized by subscription type and delivery channels. Every clause adds operational detail (OAuth requirement, feed default, channel specifics) with no redundancy.

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?

No output schema exists, yet the description covers return value, allowed types, parameter shapes, delivery mechanisms, verification prerequisites, and edge behaviors. Given the tool's complexity (3 params, nested objects, multiple channels), this is remarkably complete.

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 schema already has 100% coverage, but the description adds substantial extra meaning: concrete examples for each type (sec_8k item codes, polymarket topic, fred_series), delivery channel options with verification details, and HMAC signing mechanics. This goes well beyond the schema's 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 opens with a specific verb phrase 'Create a proactive monitoring subscription to a live-data event stream' and immediately states the return value. It clearly distinguishes itself from siblings like list_subscriptions and unsubscribe by focusing on creation of a persistent subscription.

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 explicit context on when to use this tool: for proactive monitoring of live-data streams, with a required OAuth account. It names alternative consumption methods for the feed ('recent_alerts or GET registry.pipeworx.io/alerts.json') and specifies prerequisites for email/SMS/webhook delivery. However, it does not explicitly state when NOT to use subscriptions versus one-time queries.

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 set contains many overlapping research and prediction-market tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, bet_research, polymarket_arbitrage, polymarket_edges, etc.) whose boundaries are hard to distinguish despite long descriptions. The PDL enrich tools and memory tools are clear, but an agent would frequently struggle to choose the right query or market-scanning tool.

Naming Consistency2/5

Naming conventions are mixed: there are consistent prefixes like pdl_ and polymarket_, but also arbitrary noun phrases like entity_profile, recent_changes, and bare verbs like remember, forget, and subscribe. There is no consistent verb_noun or action_resource pattern across the toolset.

Tool Count2/5

33 tools is above the recommended range and spans several unrelated domains: PDL enrichment, Pipeworx data lookup, prediction markets, memory, subscriptions, and npm dependency scanning. This feels like several servers merged together rather than a well-scoped toolset.

Completeness1/5

For a server named Peopledatalabs, the PDL surface is severely incomplete: only pdl_person_enrich and pdl_company_enrich are provided, with no PDL search, identify, or list tools. The vast majority of tools are unrelated to PDL, so an agent expecting reasonable PDL API coverage would hit dead ends immediately.

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