Skip to main content
Glama
HappyMonkeyAI

article-research-mcp

plan_article_research

Creates a structured research plan for a given topic, outlining steps, tool order, and output paths with configurable depth (quick, standard, or deep).

Instructions

Return a structured research plan for agents (steps, tool order, output paths). depth: quick | standard | deep

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
depthNostandard
tagsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so description must disclose behavior. It only mentions returning a plan, with no details on side effects, permissions, rate limits, or error handling. The tool appears read-only, but this is unstated.

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 extremely concise: one sentence and a line listing depth options. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 3 parameters and an output schema, the description falls short. It explains only depth partially, ignoring topic and tags. Users/agents lack full understanding of usage.

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

Parameters2/5

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

Schema has 0% description coverage. The description only adds meaning for the depth parameter by listing possible values (quick, standard, deep), but does not explain the required topic parameter or the optional tags parameter.

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 returns a structured research plan for agents, specifying steps, tool order, and output paths. However, it does not differentiate from sibling tools like build_topic_brief, which may produce similar plans.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, scenarios, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HappyMonkeyAI/article-research-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server