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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action and use case; it does not mention side effects, required permissions, visibility defaults, or that the post will be publicly visible. For a mutation tool, this is a significant transparency gap.

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 short sentences, front-loaded with the core action and immediately followed by relevant use cases. Every word earns its place; no fluff or unnecessary detail.

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 no output schema and no annotations, the description covers the basic purpose and use cases, and the schema fully documents parameters. However, the description lacks behavioral context (e.g., visibility defaults, auto-generated hashtags are only in schema) and does not explain what happens after posting, making it adequate but not fully complete for a 6-parameter mutation tool.

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% since all 6 parameters have descriptions, so the baseline is 3. The description adds minimal value beyond the schema, such as reinforcing that articleUrl is the link to share, but it does not introduce new parameter context that the schema already provides.

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 action ('Create') and resource (LinkedIn post with article/link), and differentiates from siblings like linkedin_create_image_post by specifying article sharing. It even provides concrete use cases (blog posts, news articles), making the tool's purpose unmistakable.

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 provides clear context for when to use the tool ('Great for sharing blog posts, news articles, or any web content'), which implies its appropriate use case. However, it does not explicitly mention when not to use it or call out alternatives like linkedin_create_post for text-only posts, preventing a 5.

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, the description handles disclosure by noting that hashtags are appended, AI generation is photorealistic, and text overlays/logos are discouraged. It does not mention permissions, publication timing, or error behavior if multiple image sources are supplied, which would improve transparency.

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: the first states the primary action and constraint ('exactly one image'), the second lists the supported image sources. It is front-loaded and contains no 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 an 8-parameter create tool with full schema coverage, the description provides a solid overview of the image modes and the posting action. It does not explain behavior when multiple image sources are provided or specify output, but these are not essential for initial invocation.

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% with detailed descriptions for every parameter, so the baseline is 3. The description's summary of the four image modes adds minor value by confirming the alternatives, but the schema already conveys a mutual exclusivity via 'Use this instead'.

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 creates a LinkedIn post with exactly one image, and explicitly lists the four supported image sources (local file, URL, search query, generation prompt). This distinguishes it from sibling tools like linkedin_create_post (text-only) and linkedin_create_article_post (articles).

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 for single-image posts and provides explicit guidance on image source options, with parameter-level 'Use this instead' instructions. However, it does not explicitly name alternative tools or state when not to use this tool, leaving some ambiguity.

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 discloses the core action (create) and visibility options, but does not mention authentication requirements, side effects, or the irreversible nature of posting. It adds some context but lacks depth.

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 core purpose, and every word earns its place. No fluff or redundancy.

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 of the tool (3 parameters, no output schema), the description provides enough context for an agent to understand the tool's function and key options. It could mention posting behavior or response, but the schema covers parameters adequately.

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%, so the baseline is 3. The description adds semantic value by explaining what each visibility value means (e.g., CONNECTIONS = 1st degree connections only), which goes beyond the schema's simple enum listing.

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 and resource: 'Create a text post on LinkedIn.' It distinguishes from sibling tools by explicitly saying 'text post,' which differentiates it from create_article_post and create_image_post.

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 specifies this is for text posts, implying it should be used for that purpose rather than article or image posts. However, it does not explicitly name alternatives or state when not to use, so it falls just short of a 5.

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?

No annotations are provided, so the description carries full responsibility for disclosing behavioral traits. It only states the action 'delete' without explaining whether the deletion is permanent, whether it requires specific permissions, whether the post must belong to the authenticated user, or what errors may occur.

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 sentence with no unnecessary words. It conveys the essential purpose efficiently.

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 one parameter, but the description lacks important context for a destructive operation, such as whether deletion is reversible, required permissions, or behavior when the post does not exist. While the core action is clear, the absence of any safety or precondition information leaves it incomplete.

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 input schema already fully describes the single parameter (postId) with a clear description. The tool description adds no extra semantic meaning beyond restating 'by its ID,' so the baseline score of 3 is appropriate given 100% schema coverage.

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 identifies the action ('Delete') and the resource ('a LinkedIn post by its ID'). This is distinct from sibling tools like linkedin_get_posts and linkedin_create_post, which perform different actions.

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 states the action but gives no explicit guidance on when to use it versus alternatives. It is implied that this tool is for deleting posts, but no context about prerequisites, ownership, or when not to use it is provided.

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, the description carries the full transparency burden. It adds a useful note about additional API permissions but does not disclose return format, safety guarantees, or other behavioral details.

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 short, focused sentences: the first states the purpose, the second adds a necessary permission caveat. No superfluous content.

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 parameterless tool with no output schema, the description adequately conveys what the tool does and a key prerequisite. Nothing essential is missing given the tool's simplicity.

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 tool has zero parameters, so the schema is fully covered. Baseline of 4 is appropriate because there are no parameter details to add.

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's function with a specific verb ('Get') and resource ('number of LinkedIn connections'), distinguishing it from sibling tools that handle profiles and 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 purpose is self-evident, implying usage when the connection count is needed. The permission note provides a prerequisite but the description does not discuss alternatives or when not to use this tool.

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?

No annotations are provided, so the description carries the full transparency burden. It discloses a potential authorization requirement ('may require additional API permissions') and scope (authenticated user), but does not mention read-only nature, return structure, or error behavior. Adds some value beyond schema.

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 sentence contains the core purpose and a permission caveat. No fluff, no repetition, and it is front-loaded with the main verb and resource.

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 read-only tool with one optional parameter and no output schema, the description is adequate. It states what it gets and notes a key prerequisite (permissions). Missing details like return format are not critical given the simplicity.

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%: the 'count' parameter is fully described in the input schema with default and max. The description adds no additional parameter semantics beyond what the schema already states, so baseline 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?

Description uses specific verb 'Get' and resource 'authenticated user's recent LinkedIn posts', clearly distinguishing from sibling create/delete tools. It is unambiguous and defines exactly what the tool returns.

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?

Description implies usage for reading the user's own posts, but provides no explicit when-to-use guidance or exclusions compared to sibling tools like create/delete. There is no mention of alternatives or when not to use this tool.

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?

No annotations are provided, so the description must carry the burden of transparency. It discloses that the profile is the authenticated user's, implying OAuth context, but does not mention read-only status, potential errors, or side effects. This is moderate transparency for a 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 a single, clear sentence with no filler words. It front-loads the verb and resource, and every word adds meaning. Highly concise and well-structured.

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 tool with no parameters and no output schema, the description provides the essential context: what data is returned. It could be improved by mentioning the response format or any authentication prerequisites, but it is complete enough for a simple profile getter.

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 tool has zero parameters, so there are no parameter semantics to explain. The description adds value by listing what the returned profile includes, which serves as the output semantics. Baseline 4 is appropriate for zero-parameter tools.

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 action (get), the resource (authenticated user's LinkedIn profile), and specific included fields (name, email, profile picture). It distinguishes itself from sibling tools that focus on posts and connections count.

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 when the authenticated user's profile data is needed, but it does not explicitly mention when to use this tool over alternatives or any exclusions. Since siblings are clearly different, the implied usage is acceptable but not explicit.

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