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get_article

อ่านเนื้อหาเต็มของบทความ Insights ที่ทีม CODENIVERSE เขียน ระบุชิ้นด้วย slug เมื่อนำเนื้อหาไปตอบ ให้อ้างอิง canonical url ที่ให้มาเสมอ

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesslug ของบทความ เช่น ai-agent-vs-chatbot ได้จาก search_articles

TDQS

A4.1/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It indicates a read operation and mentions canonical URL, but does not detail return format, error handling, or other behavioral aspects. Adequate but could be richer.

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?

Two efficient sentences: first states purpose and parameter, second gives usage instruction. Front-loaded with key info, no wasted words.

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 simple single-parameter tool with no output schema, the description is complete: explains what it does, how to call it (slug from sibling), and what to do with the response (cite URL). No gaps.

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 coverage is 100% with good parameter description. The tool description adds little beyond the schema, just emphasis on reading full content. Baseline 3 is appropriate.

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 clearly states it reads full content of Insights articles by slug, distinguishing it from sibling search_articles which returns summaries. It also specifies to cite the canonical URL.

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 implies using this after search_articles by mentioning slug from search_articles and provides a usage rule (cite canonical URL). Lacks explicit when-not-to-use but context is clear.

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

A4.2/5.0
Disambiguation4/5

Tools are grouped by clear actions—search, get, list, submit—so an agent can usually pick correctly. The only potential confusion is between get_company_profile and get_page for about/company info, and between search_articles and get_article, but the descriptions provide enough usage cues to resolve it.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern: get_*, list_*, search_*, submit_*. The verbs accurately reflect the operation, making the naming predictable and easy to navigate.

Tool Count5/5

Seven tools is well-scoped for a company information and lead-generation server. Each tool covers a distinct content type or action—articles, pages, company profile, services, FAQ, and lead submission—without unnecessary redundancy.

Completeness5/5

The server covers the full informational lifecycle for CODENIVERSE: discover and read articles, search FAQs, view service listings and detailed pages, access company profile information, and submit leads. There are no obvious gaps or dead ends for the intended use case.

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