self-hosted-ai

list_articles

Read-onlyIdempotent

List all blog articles. No TF-IDF computation — pure database listing.

Use to browse the full corpus, paginate through articles, or filter by tag.
For full-text semantic search use search_blog instead.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`tag`	No	Optional tag filter (e.g. 'setup', 'fixes', 'strategy'). Only articles with this tag are considered. Use list_tags to discover available tags.
`sort`	No	Result ordering. 'date_desc' newest first (default). 'date_asc' oldest first. 'title_asc' alphabetical. 'quality_desc' best quality first.	date_desc
`limit`	No	Number of results (1-50)
`offset`	No	Pagination offset (0-based)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 21, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds valuable behavioral context beyond annotations by stating it is a pure database listing with no TF-IDF computation, which informs performance expectations and distinguishes it from heavier search operations.

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 concise sentences deliver purpose, usage, and alternative routing with zero redundancy. The key behavioral distinction is front-loaded, and every 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 read-only listing tool with a full output schema, documented parameters, and annotations covering idempotency, the description is complete. It gives an agent everything needed to select the tool correctly and understand its scope without unnecessary detail.

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?

Schema description coverage is 100%, so the schema fully documents all four parameters. The description mentions filtering by tag and pagination but adds no parameter-level detail beyond what the schema already provides, so the baseline score of 3 applies.

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 verb and resource ('List all blog articles') and immediately distinguishes the tool's behavior from semantic search by noting 'No TF-IDF computation — pure database listing.' This clearly separates it from search_blog and other siblings.

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?

The description explicitly states when to use this tool ('browse the full corpus, paginate through articles, or filter by tag') and names the alternative for when not to use it ('For full-text semantic search use search_blog instead'). This gives an agent direct routing 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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