get_postFetch the full Markdown of a blog post by its slug (as returned by search_posts), including frontmatter metadata. Returns clean, agent-readable Markdown.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Post slug, e.g. "rag-vs-fine-tuning-llms-2026". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries some burden. It discloses the return format ('clean, agent-readable Markdown') and includes frontmatter metadata, which is useful. However, it does not mention potential errors, permissions, or rate limits, leaving some behavioral gaps.
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?
Two concise sentences start with the primary action and include only relevant details (Markdown, frontmatter, agent readability). No 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 simplicity (1 param, no output schema) and lack of annotations, the description covers the key aspects: input, source, return format, and content type. It could mention behavior on missing slugs, but overall it's sufficiently complete for a basic fetch operation.
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 provides full coverage of the slug parameter with an example. The description adds the context that the slug comes from search_posts, which clarifies the expected input source, enhancing the schema.
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 clearly states the verb 'Fetch' with the resource 'full Markdown of a blog post' and specifies the identifier (slug). It distinguishes from siblings like search_posts by mentioning that the slug comes from there, and from get_profile/list_topics by focusing on blog post content.
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?
It implies the workflow of first using search_posts to get a slug, then get_post to retrieve content. However, it does not explicitly state when not to use it or compare with listing topics/profile, so it lacks explicit exclusions.
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.
Each tool has a clearly distinct purpose: fetching a specific post by slug, retrieving the profile, listing topic hubs, and searching posts. There is no overlap or ambiguity in their roles.
All tool names follow a consistent verb_noun pattern in lowercase snake_case (get_post, get_profile, list_topics, search_posts). No deviations or mixed conventions.
Four tools is well-scoped for a personal blog and profile server. Each tool covers a distinct, necessary function, and the count feels neither sparse nor excessive for the domain.
The server provides complete read-only coverage for its purpose: searching posts, retrieving full posts, listing topic hubs, and accessing the profile. There are no obvious gaps in the content-access lifecycle.