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Glama

Nws

by io.github.pipeworx-io

Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

Schema Changelog

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

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive. The description adds behavior like returning raw payload, mark_read affecting future calls, and polling being fine. Provides context beyond annotations.

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?

Five well-structured sentences with no redundancy. Front-loaded purpose, then parameter details, then usage advice. Every sentence adds value.

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?

For a 5-parameter tool with no output schema, the description covers return contents, filtering, mark_read behavior, polling suitability, and alternative access. Feels complete for its complexity.

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% with descriptions. The description adds semantic details like example type ('sec_8k') and explains mark_read effect. Enhances understanding beyond 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 it pulls fired events from the subscription feed, returns most recent alerts with source, citation_uri, and payload. It distinguishes from siblings by mentioning the alternative REST endpoint and focusing on feed-based alerts.

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 filtering by type and since, setting mark_read for read tracking, and mentions polling suitability. However, it does not explicitly state when not to use this tool or compare with similar siblings like get_alerts.

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

A3.7/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., multiple Polymarket analysis tools, several query tools (ask_pipeworx, deep_research, compare_entities, entity_profile) with unclear boundaries. Agents may struggle to choose the correct tool.

Naming Consistency3/5

While most names use snake_case, there is no consistent prefix pattern across subdomains (e.g., 'ask_', 'get_', 'polymarket_', 'pipeworx_'). Some names like 'bet_research' and 'deep_research' follow different conventions within the same domain.

Tool Count2/5

34 tools is excessive for a server named 'Nws' that primarily suggests weather. The set covers many unrelated domains (prediction markets, npm scanning, memory), making the scope unfocused and overloaded.

Completeness3/5

The server has decent coverage for prediction markets and company financials, but weather tools are limited to basic forecasts/alerts, lacking radar, climate, or historical data. Other domains like npm scanning seem tacked on.

Resources