blog

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

No annotations are provided, so the description carries full responsibility. It discloses the return format ('full Markdown body') which adds useful context, but omits details like error behavior, authentication needs, or read-only safety. This is minimal but non-tautological.

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 a single sentence, front-loaded with the verb and resource, with no wasted words. It perfectly captures the tool's essence.

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 simple retrieval tool with one parameter and no output schema, the description covers the purpose and return type adequately. It does not mention not-found behavior or error handling, but for a basic getter this is a minor gap.

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 parameter description includes a concrete example. The tool description's 'by slug' adds no new meaning beyond what the schema already 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 clearly states the tool fetches a specific blog article's full Markdown body by slug. It distinguishes from siblings list_articles and search_articles by indicating this is for a single known article.

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 context is clear: use this tool when you have a specific slug and need the full Markdown body. It doesn't explicitly mention using list_articles or search_articles to discover slugs, but the phrasing 'specific blog article by slug' implies that prerequisite.

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

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

With no annotations provided, the description carries the full burden. It does disclose that the tool lists all articles and what fields are returned, indicating a read-only, broadly scoped operation. However, it omits details about pagination, ordering, or potential error conditions, which are useful for a full behavioral picture.

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 a single, clear, front-loaded sentence with no redundancy. Every word contributes to the tool's purpose and output characteristics.

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 simple list tool with one optional parameter and no output schema, the description covers the returned fields adequately. However, it lacks guidance on how it differs from search_articles and get_article, and does not mention potential behavioral caveats like pagination, making it only minimally complete.

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 for the single 'tag' parameter is 100%, and the description adds no extra meaning beyond the schema. The baseline of 3 applies because the schema already adequately documents the parameter.

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 uses a specific verb 'List' with a clear resource 'all blog articles' and enumerates the returned fields (slug, title, description, date, tags, reading time). The explicit 'all' distinguishes it from siblings get_article (single article) and search_articles (search behavior).

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 implies use when you want all articles, but it does not explicitly state when to prefer this over search_articles or get_article, nor does it mention any exclusions or preconditions. The guidance is only implied by the word 'all'.

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

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

With no annotations provided, the description carries the burden. It discloses the search scope, the fact that results are filtered, and the presence of a relevance score. This is sufficient for a simple read-only search tool, though it omits details like pagination or authorization requirements.

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 two sentences, front-loaded with the primary function, and contains no redundant or unnecessary information. Every word contributes to understanding the tool's purpose and output.

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?

The tool is simple with a single parameter and no output schema. The description adequately covers the tool's behavior and return value. A missing note on pagination or sorting is a minor gap, but overall the description is complete for typical use.

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 provides 100% coverage with the query parameter description 'Search terms', so baseline is 3. The tool description adds meaning by explaining what the query is matched against (titles, descriptions, tags, bodies), which gives context beyond the schema's terse description.

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 a specific verb ('search'), resource ('articles'), and scope (titles, descriptions, tags, bodies). It also mentions the return of relevance scores, which distinguishes it from sibling tools like get_article (single retrieval) and list_articles (bulk listing).

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 implies usage for full-text search across article fields but does not explicitly state when to use this tool vs alternatives, nor does it provide exclusions or compare with siblings. Context like 'use list_articles for browsing all articles' is absent.

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