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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

A3.8/5.0
Behavior1/5

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

The annotation readOnlyHint=true conflicts with the description's statement that setting mark_read:true will 'flag returned events read', which is a state mutation. The description discloses this side effect, but the annotation contradicts it, triggering the annotation contradiction rule. This is a serious inconsistency that could mislead an agent about the tool's side effects.

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?

The description is well-structured, front-loaded with the primary purpose, and every sentence provides useful information—return fields, filters, read-state behavior, and alternative access. 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?

It explains return payload contents (source, citation_uri, raw payload) despite no output schema, and mentions polling suitability and an HTTP alternative. It does not explicitly mention the 'unread_only' parameter, but the schema covers it, so this is a minor gap. Overall, it is quite complete for a read-focused tool.

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?

Although schema coverage is 100%, the description adds value by giving a concrete example for type ('sec_8k'), reinforcing the ISO format for since, and explaining the behavioral effect of mark_read (only newer events on next call). This goes beyond the basic schema descriptions.

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 action ('Pull fired events from your subscription feed') and clearly identifies the resource (persisted alert feed). It distinguishes this from sibling tools like recent_changes or list_subscriptions by focusing on fired alerts with filtering and read-state management.

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 clear context for usage: you can filter by type/since, set mark_read, and poll the same feed via an HTTP endpoint for scripts. However, it does not explicitly state when to use this over sibling tools like recent_changes or when not to use it, so it falls short of a perfect 5.

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

A3.5/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx and ask_pipeworx_beta are explicitly identical, ask_pipeworx_grounded and deep_research both route queries to the same 5,529 tools, and ai_visibility_check vs scan_competitor_ai_presence are near-duplicates. Only the small ga_* subset is clearly distinct.

Naming Consistency2/5

Conventions are mixed: GA tools use a ga_ prefix, but the majority use arbitrary names like ask_pipeworx, deep_research, remember, scan_dependency, and polymarket_arbitrage. No consistent verb_noun pattern across the set.

Tool Count2/5

35 tools is heavy, and the vast majority (31) are unrelated Pipeworx utilities rather than Google Analytics functionality. Only 4 tools actually serve the stated GA purpose, making the count inappropriate for the server name.

Completeness2/5

For Google Analytics, the surface is minimal: list properties, metadata, realtime, and run report—no property management, user management, or data mutation. As a Pipeworx toolkit it's broad but lacks full lifecycle coverage for any single domain.