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list_articles

List all articles on loopingagent.com (technical blog: agentic AI, MCP, TypeScript, blockchain). Returns slug, title, category and excerpt for each. Optional category filter (agentic-ai | blockchain).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoFilter articles by category.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It clearly indicates a read-only listing operation ('List') and discloses the exact return shape (slug, title, category, excerpt), plus the category filtering behavior. It does not mention pagination or ordering, but neither is critical for a simple blog-list tool.

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 short sentences with no filler: purpose is front-loaded, return fields follow, and the filter option is last. Every sentence adds useful information.

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 single-optional-parameter list tool with no output schema, the description supplies everything needed to call it correctly: what it lists, what it returns, and how to filter. No other context is essential.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already fully documents the category parameter with enum values and a filter description (100% coverage). The description adds only optionality and repeats the enum values, which is useful but not a significant semantic addition over 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 names a specific verb ('List'), a specific resource ('all articles on loopingagent.com'), and the returned fields. It clearly distinguishes from siblings like get_article by framing this as the plural list operation.

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 makes the usage context explicit: call this when you need all articles, optionally filtered by category. It does not explicitly contrast with get_article for full single-article retrieval, so it stops short of the top score.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0
Disambiguation5/5

Each tool maps to a distinct resource and action: booking a call, viewing one article, viewing the profile, viewing skills, and listing articles. While get_profile includes a Cal.com link, book_call is clearly the purpose-specific tool for scheduling, so there is no real ambiguity.

Naming Consistency5/5

All tool names follow a consistent lower_snake_case verb_noun pattern: book_call, get_article, get_profile, get_skill, list_articles. Singular get_* tools and the plural list_articles follow an intuitive, predictable convention.

Tool Count5/5

Five tools is well-scoped for a personal website/portfolio server. Each tool covers a meaningful surface area without redundant or filler operations.

Completeness5/5

The toolset covers the core visitor and agent needs: discovering and reading article metadata, retrieving the profile and contact details, assessing skills, and booking a call. Article content is intentionally available via the returned canonical URL, so there are no dead ends.

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