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reports_index

Fetch the latest 12 weekly Alpha report titles, summaries, and dates. No authentication required, so AI agents can share recent report topics with users.

Instructions

Weekly reports index — titles, summaries and dates (public, MCP-compatible) — Returns a public index of the last 12 weekly Alpha reports: title, a short plain-text summary (≤300 characters), the publish date, and the week covered. Full report content (HTML in 5 languages) remains Pro-only on GET /api/content/weekly-reports. AI agents can use this endpoint to inform users about recent report topics and dates without any authentication. Response: { reports[], total, updatedAt }. Each report: id (string), title (string), summary (string, ≤300 chars), publishedAt (ISO-8601), weekOf (YYYY-MM-DD). No authentication required. Cached 1 hour (reports are generated weekly). 60 requests/min rate limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Addedv0.1.2

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses authentication requirements, a 1-hour cache, a 60 requests/min rate limit, and the fact that reports are generated weekly, all beyond what the schema or annotations could convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core statement is front-loaded, and the supporting details (response shape, caching, rate limit) are all relevant. It is slightly redundant with 'without any authentication' and 'No authentication required' both appearing, but overall it is well-organized and each sentence earns its place.

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 zero-parameter, no-output-schema, no-annotation tool, the description is fully complete. It covers the result structure, field types, limits, authentication, caching, and the boundary with the Pro-only endpoint, leaving no practical gap for an agent deciding to call it.

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 zero parameters, so the baseline is 4 and the description adds no parameter confusion. It compensates further by documenting the exact response shape and field formats, which is useful given there is no output 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?

States a specific action and resource: returns a public index of the last 12 weekly Alpha reports, with fields enumerated (title, summary, publishedAt, weekOf). It clearly differentiates itself from the Pro-only full-content endpoint, so an agent can tell exactly what this tool provides.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says AI agents can use this endpoint to inform users about recent report topics and dates without authentication, and explicitly says full report content remains Pro-only on GET /api/content/weekly-reports. This gives both a when-to-use and a when-not-to-use signal with a named alternative.

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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