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

With no annotations, the description carries the full burden, and it delivers useful behavioral context: it states the tool is a read-only query ('Get', 'Returns'), gives the 0-5 score range, lists risk flags, and identifies the source as SkillsIndex static analysis. It does not describe error behavior or dependencies, but the core side-effect-free nature is clear.

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 action, and every clause adds relevant information (score, risk flags, audit summary, source). No filler 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?

The description adequately covers the tool's return value, but given no annotations and no output schema, a bit more context would help—for example, clarifying that either name or slug must be provided, or noting that this is a read-only lookup. The tool is simple, so this is not severely incomplete, but there are clear gaps.

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%, with both parameters already fully described in the input schema. The tool description adds no specific parameter-level semantics beyond the schema, so the baseline 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 uses a specific verb ('Get') and resource ('security score and audit notes for a specific tool'), clearly distinguishing this from siblings like get_tool (general tool info) and compare_tools (comparison). It also specifies the exact output scope, removing ambiguity.

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 a user needs a tool's security assessment and audit details, but does not explicitly state when to prefer this over get_tool or search_tools, nor does it provide exclusions or alternatives. The context is clear but not fully spelled out.

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 must convey behavioral traits. It lists the output fields (scores, stars, pricing, maintenance) but does not mention whether data is fetched live, potential errors, or any side effects. It is a read-only comparison, but that is inferred rather than explicit.

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 sentences, front-loaded with the core functionality and immediately followed by the output details. Every word earns its place 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?

Given a single parameter and no output schema, the description sufficiently explains what the tool returns (overall scores, GitHub stars, pricing, maintenance status). It omits error handling or invalid-slug behavior, but for a comparison tool of this simplicity, the coverage is solid.

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 an adequate description of the 'slugs' parameter, which already specifies array of strings and example. The tool description reinforces the 2-5 limit but adds no additional semantic detail 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 clearly states the verb 'Compare' and the resource ('2 to 5 tools') with specific criteria (scores, stars, pricing, maintenance). It distinguishes this from sibling tools like get_tool and search_tools by focusing on side-by-side comparison.

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 phrase 'Use this to help a user choose between alternatives' gives explicit context for when to invoke the tool. It does not enumerate exclusions, but the 2-5 slug limit implies it is not for single-tool lookup, and sibling names indicate alternatives exist.

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 full burden of behavioral disclosure. It only says 'top' without explaining how ranking is determined, and it omits details about return format, pagination, or any access requirements. The description is essentially just a purpose statement with no additional behavioral traits.

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 front-loaded with the action and resource, and the second sentence provides clear usage context. The parenthetical platform list is somewhat long but informative. Overall, there is no fluff, but a more compact structure could reduce redundancy with the schema enum.

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 only two parameters, and the description covers the core purpose and usage. However, with no output schema and no annotations, it does not describe the response shape or the meaning of 'top,' leaving an agent to infer those details. It is minimally viable but lacks comprehensive context.

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 baseline is 3. The description adds human-readable platform examples (e.g., 'local/open-source') and suggests the filter semantics, but it does not add new technical meaning beyond the schema's enum and limit 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 uses the specific verb 'List' and clearly identifies the resource: 'top AI agent tools that work on a specific platform.' It distinguishes itself from siblings by focusing on platform-specific filtering, and the usage phrase 'when the user runs a specific agent or editor' further clarifies its niche.

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 states when to use the tool: 'Use this when the user runs a specific agent or editor.' However, it does not discuss when not to use it or name alternatives such as search_tools or get_top_rated, so it stops short of full exclusions.

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 of behavioral disclosure. It lists what the tool returns (security score, GitHub stats, install instructions, scoring breakdown), which is useful. However, it does not explicitly state that it is a read-only operation or mention any external dependencies or rate limits. The 'Get' verb implies safety, but the lack of explicit disclosure prevents a higher score.

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, well-structured sentence that immediately states the tool's purpose, provides an example, and lists the returned content. No wasted words.

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 tool with one required parameter and no output schema, the description is complete. It explains what the tool does, what the slug is, and what details are included in the response, fully equipping an agent to invoke it correctly.

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%, as the single parameter 'slug' is fully described in the schema. The description repeats the example but adds no new parameter semantics beyond what the schema already provides, so a 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 clearly states a specific verb ('Get') and resource ('full details for a specific tool by its slug'), with an example. It distinguishes itself from sibling tools like search_tools (searching) and compare_tools (comparing) by focusing on fetching a single tool's comprehensive details.

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 conveys a clear usage context: use when you need full details of a specific tool by its slug. It does not explicitly mention alternatives or when-not-to-use, but the context is clear enough to guide selection among siblings.

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 convey behavioral traits. It discloses the sorting behavior and optional filters, but does not detail return format, pagination, or other limitations. The open-ended nature of 'top-rated' leaves some uncertainty about the output structure, though the schema partially compensates for parameter-related behavior.

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 exceptionally concise: two short sentences, front-loaded with the core action and resource. The sorting information and filter options are presented efficiently without any redundant wording.

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 listing tool with no output schema, the description covers the essential context: source, sorting, and filters. It does not explicitly state the return shape, but the tool's simplicity and the schema's parameter documentation make this a minor omission, leaving it sufficiently 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 input schema provides comprehensive descriptions for all three parameters, including enums and limits, so the baseline is 3. The description only restates that filtering is optional, adding no new semantic value beyond what the schema already offers.

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'), identifies the resource ('top-rated AI agent tools from SkillsIndex'), and specifies the sorting by overall score (0-100). It also mentions optional filters, which further distinguishes it from sibling tools like search_tools or get_tool.

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 this tool: to retrieve top-rated tools sorted by score, with optional ecosystem or category filtering. It does not explicitly mention alternatives or exclusions, but the purpose is unambiguous enough to guide the agent's choice.

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. It discloses that results are ranked and include scores, which is a behavioral trait. However, it does not mention potential limits, error handling, or authentication requirements. The disclosure is present but minimal.

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, well-structured sentence that front-loads the core purpose and includes the return type. No superfluous words or repetition.

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 has no output schema, so the description should explain return values more thoroughly. It only mentions 'ranked results with scores' without describing the result object structure or content. However, the tool is relatively simple and the schema covers parameter details, making it moderately 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% for all four parameters, so the baseline is 3. The description adds no extra parameter-level meaning beyond what the schema already provides. It does not explain how 'query' is matched or how filters interact.

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 ('Search the SkillsIndex directory'), the resource ('AI agent tools'), and the output ('ranked results with scores'). This distinguishes it from sibling tools like get_tool (which likely retrieves a single tool) and compare_tools (which likely compares tools).

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 (searching for tools) but does not explicitly mention alternatives or exclusion criteria. Sibling tool names suggest other use cases, but the description itself lacks explicit guidance like 'use get_tool when you know the exact ID'.

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 of disclosing behavioral traits. It reveals that submissions undergo review for security, utility, maintenance, and uniqueness before publication, setting expectations that this is not an immediate, guaranteed listing. It doesn't cover response format or failure cases, but the review process disclosure is meaningful context.

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 sentences with no filler. The first sentence front-loads the purpose, the second adds usage context. Every word 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 5-parameter submission tool with no output schema, the description covers purpose, usage trigger, and post-submission review process. It is adequately complete for an agent to decide when and how to invoke it, though it doesn't describe the response shape or potential errors.

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 covers all 5 parameters with descriptions and enums (100% coverage), so the description is not required to add parameter-level detail. It doesn't, and baseline 3 is appropriate since schema does the heavy lifting.

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 ('Submit'), the resource ('a new AI agent tool to SkillsIndex'), and the purpose ('indexing and scoring'). It distinguishes itself from sibling tools like get_tool, search_tools, and compare_tools by being the submission entry point.

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?

Provides an explicit when-to-use condition: 'Use this when you discover a useful tool that isn't in the directory yet.' While it doesn't name alternative tools for checking existence, the conditional phrasing implies checking the directory first, giving adequate 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 full burden. It states the action (subscribe) and the subject (email) but does not disclose side effects such as confirmation emails, idempotency, data handling, or potential errors. However, the core behavior is clear, and the description adds context about the newsletter's content. It's adequate but lacks deeper behavioral detail.

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, well-structured sentence that includes the action, target, source, and newsletter content. Every word adds value; there is no fluff or repetition. It is concise yet informative.

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 one-parameter subscribe tool, the description covers the essential purpose and gives context about the newsletter. It lacks details about post-subscription behavior (e.g., welcome email, unsubscribe instructions), but these are not critical for invoking the tool. The given schema is sufficient, and the description is adequate for a typical use case.

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 covers 100% of the parameter documentation, with the 'email' property described as 'Email address to subscribe.' The description adds no additional semantic value beyond naming the recipient type ('user email'), which is redundant. Baseline 3 is appropriate for full 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 uses a specific verb ('Subscribe') and clearly identifies the resource ('a user email to The Weekly Index newsletter from SkillsIndex'). It also differentiates from sibling tools by focusing on newsletter subscription rather than tool search/compare/submit operations.

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 about the newsletter's content (weekly digest of AI agent tools, security alerts, and honest picks), making it obvious when subscription is appropriate. It doesn't explicitly state when not to use it, but the purpose is unambiguous. No exclusions are mentioned.

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 burden. It reveals the ordering ('newest first') but does not disclose any other behavioral traits such as whether pagination is supported (aside from the limit parameter), what fields are returned, or whether results include usage/security details. This is a minimal disclosure for a non-trivial list endpoint.

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 sentences, front-loaded with the core action and ordering, then a brief usage example. No redundancy or filler; every word 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?

The tool is simple with two optional parameters and no output schema. The description conveys the item type (AI agent tools), the source (SkillsIndex), and the ordering. It lacks a description of the return shape but the overall purpose is complete enough for a basic list endpoint given the schema covers parameter semantics.

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 provides 100% coverage with descriptions for both parameters (limit and ecosystem). The description adds no additional context about how these parameters behave or interact, so it neither enhances nor detracts from the schema. Baseline 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 clearly states the tool returns most recently added AI agent tools, sorted newest first. It uses a specific verb ('Get') and resource ('AI agent tools on SkillsIndex'), and distinguishes itself from sibling tools like search_tools and get_top_rated.

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 tells the user when to use this tool ('to discover fresh MCP servers, skills, and tools the directory just indexed'). It does not mention when not to use it or explicitly name alternatives, but the use case is clear enough for an agent to make a basic selection decision.

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