Get blog post
get_blog_postFetch the full text of one published Median blog post by its slug.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Post slug, e.g. 'how-to-switch-bookkeeping-services'. |
get_blog_postFetch the full text of one published Median blog post by its slug.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Post slug, e.g. 'how-to-switch-bookkeeping-services'. |
Changes observed during successful MCP inspections.
Input schema / properties / slug / descriptionPrevious value: -"Post slug, e.g. 'daily-close-for-startups'."New value: +"Post slug, e.g. 'how-to-switch-bookkeeping-services'."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds that the post must be published and that full text is returned, but it does not disclose behavior for nonexistent slugs or draft posts. This is acceptable but not richly transparent.
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?
A single, tightly worded sentence that front-loads the action, resource, and parameter. Every word earns its place, with no redundant phrasing or filler.
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?
For a one-parameter read-only tool with no output schema, this description is complete. The agent knows exactly what to supply (slug) and what to expect (full text of a published post), and the annotations cover the behavioral safety profile.
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?
Schema coverage is 100%, and the only parameter, slug, is already described with an example in the schema. The description references the slug as the lookup key but adds no new semantic detail beyond what the schema provides, so the baseline score of 3 is appropriate.
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 states a specific verb ('Fetch'), a precise resource ('full text of one published Median blog post'), and the identifying key ('by its slug'). This clearly distinguishes it from the sibling list_blog_posts, which would be used to enumerate posts.
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 description makes the intended context clear: use this tool when you need the full text of a single post and already know its slug. It does not explicitly name alternatives or exclusion conditions, but the wording and sibling list_blog_posts make the usage boundary obvious.
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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