Gets a full Walnai blog post by its slug, including the HTML body. Use ListBlogPosts first to discover available slugs. Returns null if the slug is not found.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The blog post slug (e.g. 'what-is-mcp-and-why-it-matters'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the return behavior for an unknown slug ('Returns null if the slug is not found') and notes the response includes the HTML body. It does not explicitly state read-only status, but the verb 'gets' strongly implies a read operation, and no side effects or auth requirements are omitted for this simple getter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, each serving a distinct purpose: purpose, usage, and edge-case behavior. It is front-loaded with the primary action and contains no filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity—one parameter and no output schema—the description provides sufficient context: it explains the resource, the identifier, the usage flow (list first), the inclusion of HTML body, and null behavior. No critical gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the sole parameter 'slug' with a clear description and example, achieving 100% coverage. The description adds no additional parameter semantics beyond what the schema provides, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Gets a full Walnai blog post by its slug, including the HTML body,' which clearly identifies the tool's action (get), resource (blog post), and identifier (slug). This distinguishes it from sibling tools like list_blog_posts, which enumerate posts rather than retrieve a single one. The addition of 'full' and 'HTML body' clarifies the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The instruction 'Use ListBlogPosts first to discover available slugs' explicitly tells the agent when to use this tool relative to its sibling, establishing a discovery workflow. It also implies that this tool is for retrieving a single known slug, not for listing. This is clear, actionable guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct, but get_about_info and get_who_is_walnai overlap heavily in describing Walnai, causing potential misselection. Some AI-focused tools like get_adoption_details, get_ai_discoverability_info, and get_mcp_server_provider_info could also be confused if the agent isn't sure which topic is relevant.
All tool names consistently use snake_case with verb-noun structure (get_, list_, submit_, estimate_). No mixed conventions or vague verbs like 'process' or 'run' exist.
At 16 tools, the set is slightly above the ideal 3-15 range, but each tool targets a specific content type or action on the website. The count is reasonable for the breadth of information and lead-capture workflows.
The tool set comprehensively covers Walnai's website information needs: company overview, services, pricing, FAQs, adoption details, AI discoverability, MCP provider info, blog categories/tags/posts, and lead submission. No obvious missing operations for its stated purpose.
