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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

A3.9/5.0
Behavior1/5

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

The description explicitly describes a state-changing side effect (mark_read flags returned events read, affecting the next call) that contradicts the readOnlyHint=true annotation. Per the rubric, this is an annotation contradiction, forcing transparency to score 1.

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?

Four sentences, front-loaded with the core purpose, then return format, filtering, and alternative access. Every sentence earns its place with no filler or 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?

Despite the annotation contradiction, the description covers purpose, return payload, filtering, mark_read behavior, polling suitability, and an alternative programmatic endpoint. Given no output schema and five optional parameters, this is remarkably complete.

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%, but the description adds meaningful context beyond the schema: an example type ('sec_8k'), ISO timestamp semantics for since, and the behavioral impact of mark_read. This enriches parameter understanding.

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 pulls fired events from the subscription feed using a specific verb and resource. It distinguishes itself from siblings like list_subscriptions and recent_changes by focusing on alerts with source, citation_uri, and raw payload.

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 for when to use: polling alerts with optional type/since filters and mark_read. It also mentions an alternative GET endpoint for scripts/dashboards, but does not explicitly exclude sibling tools, so it lacks full when-not guidance.

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
Disambiguation4/5

Tools are generally distinct in purpose, but some overlap exists between ask_pipeworx, ask_pipeworx_grounded, and deep_research. Descriptions clearly differentiate them, but an agent might still need to carefully choose.

Naming Consistency4/5

Most tool names follow a consistent snake_case pattern with clear prefixes (e.g., pipeworx_*, polymarket_*). A few names like compare_entities and validate_claim break the pattern, but overall it is predictable.

Tool Count2/5

With 40 tools, the server is overly large for a single coherent set. Many tools are meta or auxiliary, but the count exceeds the 'too many' threshold, making it hard for agents to navigate.

Completeness4/5

The tool set covers data retrieval, Chilean open data, Polymarket, memory, and monitoring comprehensively. Minor gaps exist (e.g., no direct trading for Polymarket), but the surface is complete for the stated purpose.