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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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds value by disclosing that mark_read:true will flag returned events as read, affecting future calls, and by noting the feed is persisted. This goes beyond the structured hints without contradicting them.

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?

Three sentences, front-loaded with the primary action. Each sentence earns its place: what it does, what events contain, filtering/mark_read behavior, and an alternative access method. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description summarizes return fields (source, citation_uri, raw event payload) and covers key behaviors (filtering, mark_read). It doesn't mention limit or unread_only in prose, but the schema covers those. Slight gap: no explicit pagination or error handling, but not critical.

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 description coverage is 100%, so the baseline is 3. The description adds extra meaning by giving an example type ('sec_8k') and explaining the interaction between mark_read and subsequent calls ('next call only shows newer ones'). This enriches the 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 opens with a specific verb+resource: 'Pull fired events from your subscription feed.' It clearly states what the tool returns (most recent alerts with source, citation_uri, raw payload) and thus distinguishes itself from similar read tools like recent_changes by focusing on subscription 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?

It provides contextual guidance by saying 'Polls work fine' and offering an alternative HTTP endpoint for scripts/dashboards, implying this tool is intended for agent interaction and polling. It stops short of explicitly naming sibling tools or exclusion criteria, but the context is clear.

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

B3.3/5.0
Disambiguation1/5

The server contains 4 joke-related tools and 31 tools from the Pipeworx data ecosystem, which are entirely unrelated. An agent cannot easily distinguish whether to use a joke tool or a data tool, causing extreme ambiguity.

Naming Consistency2/5

Tool names within the joke subset (e.g., get_joke, search_jokes) and Pipeworx subset (e.g., ask_pipeworx, entity_profile) are individually consistent, but the overall set has no unified naming pattern or domain signal, making the server's purpose unclear.

Tool Count1/5

With 35 tools, the count is excessive for a jokes-themed server. Only 4 tools are joke-related; the remaining 31 belong to a completely different domain, making the tool count highly inappropriate.

Completeness1/5

The joke coverage (get, search, categories, flags) is minimal but functional. However, the server as a whole is a Frankenstein of unrelated domains, lacking a coherent surface. The overwhelming majority of tools are irrelevant to the server name.