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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

A3.5/5.0
Behavior1/5

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

The annotations declare readOnlyHint: true, but the description explicitly says 'Set mark_read:true to flag returned events read so the next call only shows newer ones,' which indicates a state-changing side effect. This directly contradicts readOnlyHint, making the behavioral transparency score 1 and triggering an annotation contradiction.

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 four sentences, front-loaded with the main purpose, and each sentence adds unique value: payload contents, filtering options, mark_read side effect, and alternative access. There is no redundancy or fluff.

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?

With no output schema, the description sufficiently explains the return payload and key behaviors (filtering, mark_read, alternative endpoint). It covers the essential aspects for a 5-parameter tool, though the annotation contradiction could confuse an agent about side effects, slightly reducing completeness.

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?

The input schema has 100% parameter coverage, so the baseline is 3. The description adds value by providing an example for type ('sec_8k'), clarifying since as an ISO timestamp, and explaining the downstream effect of mark_read on future calls, which goes beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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, with details on the return payload (source, citation_uri, raw event payload). It uses a specific verb and resource, but does not explicitly differentiate from sibling tools like recent_changes, so it earns a 4 rather than a 5.

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 provides clear context by mentioning polling is supported and offers an alternative HTTP endpoint for scripts/dashboards. It implies when to use this tool (for polling) but does not discuss when to use it versus sibling tools, so it lacks explicit exclusions or alternatives.

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

A4/5.0
Disambiguation5/5

Each tool has a highly specific purpose with detailed descriptions, making them easily distinguishable. Overlaps are minimal; for instance, Pipeworx and Polymarket tools have distinct roles within their domains.

Naming Consistency4/5

Most tools follow a consistent snake_case pattern (e.g., ask_pipeworx, compare_entities), but a few single-word names (e.g., forget, recall) deviate slightly, causing minor inconsistency.

Tool Count2/5

The server is named 'recipes' but contains only 4 recipe-related tools out of 34. The majority cover unrelated domains like finance, betting, and data queries, making the scope overly broad and misaligned with the server name.

Completeness2/5

For the 'recipes' domain, essential CRUD operations and features like meal planning are missing. While the general tool set is extensive, it lacks critical recipe-related functionality, leaving significant gaps for the intended purpose.