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 source (mcp.json), the OAuth requirement for hosted URLs, and the server's limitations (no implementation, no token acceptance, no proxying). This sets accurate expectations for the agent.

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?

Three sentences, with the primary action front-loaded in the first sentence. Each sentence contributes either usage guidance or critical limitations with no 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?

For a zero-parameter tool with no output schema and no annotations, the description is complete: it explains what is returned, when to use it, and what it does not do. An agent can safely and correctly invoke the 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?

The tool has zero parameters and the schema already makes this clear with 100% coverage. The description adds no parameter details, which is fine; a baseline of 4 is appropriate for a no-parameter tool.

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 and resource: 'Return AdsAgent hosted HTTP MCP URLs from this repo's mcp.json.' This clearly states what the tool does and distinguishes it from sibling tools that operate on skills and readmes.

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 explicitly says 'Use this when a client needs the real Meta, Google Ads, or TikTok ads MCP endpoints,' and then clarifies what the docs server does not do (implement ads tools, accept tokens, proxy endpoints). This provides both a when-to-use and a when-not context.

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 present, so the description carries the full burden of behavioral disclosure. It usefully states what is returned (VERSION and README identity excerpt), what is excluded (per-skill table, secrets), and the identity nuance about the repo not being the hosted AdsAgent ads backend. It does not describe output format or error conditions, but for a zero-parameter read tool the disclosed boundaries are strong.

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 compact and front-loaded: the main action is stated in the first sentence, usage guidance follows, and boundary conditions are summarized in two short sentences. Every sentence earns its place without 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?

For a zero-parameter tool with no output schema and no annotations, the description fully covers what the agent needs: what the tool returns, its intended use, and its explicit exclusions. The nuance about the Glama/Docker image not being the hosted AdsAgent backend also prevents a plausible misunderstanding.

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 0 parameters, so parameter explanation is unnecessary. The description instead focuses on the meaningful output semantics, which is the right trade-off for an argument-less tool.

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 starts with a specific verb and resource: 'Return this skill-pack VERSION and a README.md identity excerpt.' This clearly distinguishes the tool from siblings like get_skill, get_hosted_mcp_urls, and list_skills by describing a unique output. The additional clarification about 'what this is / is not' wording further pins down its exact purpose.

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 explicitly says 'Use this to confirm pack version and the public wording,' giving a clear and direct usage context. It does not, however, name alternative sibling tools or state when not to use them, so it falls short of full exclusion guidance.

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 burden. It discloses validation behavior ('Rejects unknown skill ids and any path that leaves the skill directory'), the read-only nature ('documentation retrieval, not a live ads API'), and the progressive-disclosure contract for references. It doesn't cover errors for nonexistent reference files, auth, or rate limits, but for a simple retrieval tool these are not critical omissions.

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 sentences with zero filler. The core purpose is front-loaded in the first sentence, usage guidance follows in the second, and the final sentence provides validation and identity context. Every sentence earns its place.

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 two-parameter read-only tool with no output schema and no annotations, the description covers the key context: what is returned, when to use it, the progressive-disclosure reference convention, and validation rules. It does not specify the exact response structure or behavior when an in-folder reference file is missing, but the tool is simple enough that the description is nearly 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 description coverage is 100%, so the schema already thoroughly documents both skill_id and references, including examples and path constraints. The description reinforces these semantics with 'progressive-disclosure contracts' and the rejection of path escape, but it does not add substantial new parameter-level meaning beyond 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 opens with a specific action and resource: 'Return one skill's SKILL.md and optional named reference files.' It is clearly distinguished from list_skills (which lists skills) by saying to use it after list_skills for the full public instructions of a single skill, and from the live ads API identity statement.

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?

Explicitly says 'Use this after list_skills when you need the full public instructions for a single skill,' giving a clear when. It also instructs when to pass references (only for Markdown files in that skill folder) and that invalid ids/paths are rejected. However, it does not explicitly compare to the sibling tools get_pack_readme or get_hosted_mcp_urls, so it falls short of a full when-not/alternatives roadmap.

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 burden and does so well. It discloses that the tool 'only reads local files under skills/, does not connect to Meta, Google Ads, or TikTok and does not run campaigns,' which prevents the agent from expecting external side effects. It also describes the return contents, giving useful behavioral expectations beyond a simple 'list' label.

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 concise and well-structured, front-loading the main action and resource. Each sentence earns its place: what it returns, when to use it, and what it does not do. No redundant or vague language.

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 zero-parameter read-only listing tool with no output schema, the description is complete. It names the domain of skills, gives the intended first-use pattern, describes return fields, and explicitly scopes its behavior. An agent has everything needed to invoke it and interpret the result.

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 document. The description still usefully explains the output shape, which is more relevant for this tool. A baseline of 4 is appropriate since parameter documentation is not needed.

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 and resource: 'List public AdsAgent skills shipped in this repository.' It clearly distinguishes this catalog-listing tool from siblings like get_skill, which opens a specific SKILL.md, and from get_hosted_mcp_urls/get_pack_readme. The scope is unambiguous.

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 explicitly says 'Use this first when you need a catalog of documentation skills... before opening a specific SKILL.md,' providing a clear when-to-use directive. It does not spell out when-not-to-use or name alternatives, but the context is strong enough for an agent to select it appropriately.

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