xpay✦ DevTools Collection

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

With no annotations, the description bears full responsibility for behavioral disclosure. It states that the tool returns a structured analysis with issues and strengths, but it does not explicitly say whether the tool executes the code or performs static analysis only. Given sibling tools like execute_code and execute_code_with_variables exist, the lack of clarity about execution semantics is a meaningful 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 sentences, well-organized, and front-loaded with the primary action. Every sentence contributes meaning: the first states the scope, the second describes the return format. Zero 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?

The tool appears to be a comprehensive analysis tool with 2 simple parameters and full schema coverage, so the description is moderately adequate. It mentions the return type ('structured analysis with issues and strengths') but gives no detail about the output structure, which could be important without an output schema. It also does not clarify how it differs from the many sibling analysis tools, leaving some contextual ambiguity.

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 full description coverage for both parameters (code and filename), so the baseline is 3. The description does not add any extra context about the parameters (e.g., language detection via filename), but no compensation is needed since the schema is complete.

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 ('Analyze') with a clear resource ('code') and explicitly lists the issue categories (security, errors, deceptive patterns, placeholders). This distinguishes it from sibling tools like check_security or check_placeholders, which focus on individual categories, making the purpose 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 implies a comprehensive analysis covering multiple categories, which hints at when to use this tool over specialized siblings. However, it does not explicitly state 'use this for a full review' or mention when to prefer check_security, validate_code, etc. Usage context is implied rather than explicitly guided.

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 safety. It mentions output details (confidence levels) but does not explicitly state that the tool is read-only or that it does not execute the submitted code. This leaves behavioral ambiguity for a tool that accepts source code.

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 redundancy. The first sentence states scope, the second adds specific pattern names 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?

The description covers the core behavior and mentions output characteristics, but lacks details on supported languages, limitations, or error handling. Given the absence of an output schema, more behavioral detail would improve completeness, but for a simple analysis tool it is minimally adequate.

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 descriptions for both code and filename. The tool description adds no additional parameter-specific semantics, so it does not go beyond the schema, earning the baseline score.

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 clearly states the tool's purpose: analyze code for GoF design patterns. It lists specific patterns (Singleton, Factory, Observer, Strategy) and mentions output with confidence levels, distinguishing it from generic siblings like analyze_code or analyze_patterns.

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 GoF pattern analysis but does not explicitly state when to use it over siblings like analyze_patterns or analyze_code. No exclusion criteria or alternative tool suggestions are 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 burden of disclosing behavioral traits. It mentions the tool 'detects' and 'provides suggestions,' but does not state whether it is read-only, what side effects it has, performance implications, or failure modes. This leaves significant behavioral assumptions for a tool that analyzes arbitrary code.

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 exactly two sentences, front-loaded with the primary action ('Analyze code'), and contains no redundant or filler content. It efficiently communicates the purpose and expected 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?

Given the lack of annotations and output schema, the description is too sparse to be fully complete. It omits return value details, default behavior (e.g., level defaults to 'all'), and any guidance on usage context or limitations, especially when multiple sibling tools exist. The agent would need to infer or experiment to use this tool effectively.

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 no additional meaning beyond the schema's parameter descriptions; the mention of 'patterns' reflects the level enum but does not elaborate on parameters like query or filename. The description's outcome statements are helpful but not parameter-specific.

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: 'Analyze code for architectural, design, and implementation patterns.' It specifies the resource (code), the action (analyze), and the scope (pattern levels), and distinguishes itself from siblings like analyze_code and analyze_design_patterns by covering all pattern levels and providing actionable suggestions.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention conditions for choosing analyze_patterns over analyze_code or analyze_design_patterns, nor does it offer exclusions or prerequisites. The context is implied but not stated.

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 behavioral disclosure. It does not mention return format, side effects, or limitations. For a check tool, it should at least state that it returns findings or a status, but it only describes the analysis intent.

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, front-loaded sentence with no redundant words. It effectively communicates the core purpose and provides concrete examples ('empty catches, silent failures') without wasting space.

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 lack of annotations and output schema, the description is incomplete for an agent to fully understand the tool's behavior. It does not explain what the tool returns, what types of code it supports, or any edge cases. While the tool is simple, additional context about output would be necessary.

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 descriptions for both parameters (code and filename), achieving 100% schema coverage. The description does not add any additional parameter semantics beyond what the schema already states, 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 specifies the tool's function: checking code for deceptive patterns such as empty catches and silent failures. It uses a specific verb ('check') and resource ('code patterns'), and the focus on deceptive patterns distinguishes it from siblings like analyze_code and check_security.

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?

No explicit guidance is given on when to use this tool versus alternatives. The description implies it is for detecting deceptive patterns, but it does not name any sibling tools, provide exclusions, or state conditions under which another tool would be preferred.

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. While it lists what is checked, it does not disclose the output format, any limitations (e.g., heuristic nature), or whether the tool is read-only. The agent is left without key behavioral 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?

The description is a single concise sentence that gets straight to the point. It is front-loaded with the verb 'Check' and immediately enumerates the types of placeholders scanned. 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?

The tool is simple with only 2 parameters, both documented in the schema. However, there is no output schema, and the description doesn't explain what the tool returns, leaving a gap in completeness. The description clearly states the purpose but not the result format.

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 (code and filename) already described in the schema. The description adds no additional meaning beyond the schema, so the baseline score 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 checks for placeholder code, dummy data, TODO/FIXME comments, and incomplete implementations. This is a specific verb and resource set, making the purpose clear, though it does not explicitly differentiate from sibling tools like analyze_code or validate_code.

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 when to use the tool (when you want to check for placeholders), but it provides no explicit guidance on when not to use it or how it compares to alternatives. No exclusions or alternative tools 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 must disclose behavior, but it only states the scope of the scan (types of vulnerabilities) without explaining side effects, state changes, or the format of results. The verb 'check' implies a read-only operation, but this is not explicitly stated, nor is any output contract or limitation described.

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, tight sentence with a clear verb-object structure and no filler; it front-loads the action and scope effectively.

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 2-parameter tool with no output schema, the description would benefit from noting the return format (e.g., list of vulnerabilities with locations). It currently provides the core purpose but omits any detail about what the caller receives, which is a clear gap given no output schema exists.

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% (both code and filename have descriptions), so the baseline is 3 even without additional parameter details in the description. The description does not add further meaning to the parameters, such as how filename influences the analysis or expected input formats.

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 'check' and resource 'code', with explicit scope 'security vulnerabilities only' and examples (hardcoded secrets, SQL injection, XSS) that distinguish it from broader siblings like analyze_code or validate_code. The 'only' qualifier crisply differentiates it from general code analysis 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 phrase 'security vulnerabilities only' provides clear context for when to use this tool—when security review is the goal—and implicitly excludes non-security checks. However, it does not explicitly name alternative tools for other analysis types, so it falls short of a full when-to-use/when-not-to-use guide.

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 of behavioral disclosure. It clearly states the transform (decode to PlantUML code) but does not mention error handling, input validation, or side effects. For a simple transform, this is adequate but not rich; a more explicit note about non-mutating behavior would elevate it.

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 redundancy. It is front-loaded with the action verb and immediately conveys the purpose. 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 simple one-parameter tool with full schema coverage, the description is complete enough. It states the input and the output implicitly ('back to PlantUML code'). Since no output schema exists, the description's mention of the output helps, though it could specify the return format (e.g., UTF-8 string) for absolute clarity.

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 with a description ('Encoded PlantUML string to decode') that mirrors the tool description. The description adds no additional semantic detail 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 uses a specific verb ('decode') with a clear resource ('encoded PlantUML string') and outcome ('back to PlantUML code'). It distinguishes itself from sibling tools like encode_plantuml and generate_plantuml_diagram by explicitly stating the inverse operation.

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 you have an encoded PlantUML string. However, it does not explicitly state when to use this tool over alternatives, nor does it mention preconditions or exclusions. The sibling context suggests encode_plantuml as the inverse, but the description itself provides no direct comparison.

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 does not disclose what the encoded output looks like, whether it's a pure transformation, or any error behavior. The phrase 'for URL usage' implies a URL-safe result but lacks specifics.

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 contains no filler. It is appropriately sized for a tool with one parameter.

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 the return value, but it doesn't. It also lacks context about when to use encoding and what the output format is. For a simple tool this is still a significant 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% (the parameter is described as 'PlantUML diagram code to encode'), so the baseline is 3. The description adds no additional meaning about the parameter, such as format constraints or examples.

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 ('encode') and resource ('PlantUML code') with a clear purpose ('for URL usage'). It distinguishes from sibling tools like decode_plantuml (the inverse operation) and generate_plantuml_diagram (which creates diagrams).

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 no guidance on when to use this tool versus alternatives. It doesn't mention that decode_plantuml is the inverse or give any context about when encoding is needed, leaving the agent to infer from the name alone.

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?

There are no annotations, so the description carries the full burden. It mentions 'securely' and 'comprehensive error handling,' but lacks specifics about sandboxing, default network/memory restrictions, return formats, or error behavior. This is vague and insufficient for a code execution tool.

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 concise sentence with no redundancy. It is front-loaded with the core purpose, though some terms like 'comprehensively' are vague but do not detract significantly.

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?

Executing arbitrary code is high-risk and requires clear context. With no annotations, no output schema, and 6 parameters, the description should explain sandboxing, default behaviors, and error handling. It only provides generic claims, leaving major gaps for the agent to navigate safely.

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% across all 6 parameters, each with meaningful descriptions. The tool description adds no additional parameter semantics, 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?

Description clearly states the action ('Execute') and resource ('JavaScript or Python code'), which is specific and understandable. However, it does not differentiate from sibling tools like python_execute or execute_code_with_variables, so it falls short of a 5.

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?

No guidance is provided about when to use this tool versus alternatives, and no conditions or exclusions are mentioned. The description is purely functional, leaving the agent to infer usage 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?

With no annotations provided, the description must carry the burden of behavioral disclosure. It only explains the variable-passing mechanism but fails to disclose execution environment details, return format, error behavior, side effects, or security implications of running arbitrary code. This is a significant gap for a code execution tool.

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 that is front-loaded with the verb and resource, immediately conveying the core purpose and differentiator. Every word earns its place; there is no fluff 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?

Despite covering main parameters in the schema, the description leaves critical questions unanswered for a code execution tool: How are variables exposed to the code? What is the return format? How are errors reported? Are there sandboxing or security concerns? No output schema exists, so the description should compensate but does not.

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 schema already documents all 7 parameters. The description adds minimal extra meaning by conceptualizing 'variables' as key-value pairs, but it does not elaborate on input, timeout, memoryLimit, enableNetworking, or their defaults. 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 clearly states the verb 'Execute', the resource ('JavaScript or Python code'), and the key differentiator 'dynamic input variables' that can be passed as key-value pairs. This distinguishes it from siblings like execute_code and python_execute by focusing on variable support.

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 dynamic variables are needed, but it does not explicitly mention alternatives or exclusion scenarios. There is no guidance such as 'for simple execution without variables, use execute_code' or 'when you need networking, enable enableNetworking'.

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?

Despite having no annotations, the description discloses key behaviors: automatic syntax validation, return of embeddable URLs or structured errors, and optional local file saving. It doesn't detail side effects like overwriting files or permission requirements, but it covers the main 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?

Two sentences, no filler, front-loaded with the main action and key differentiator.

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?

With a moderate number of parameters and no output schema, the description explains the return types (URLs or error details) and optional side effect (file saving). It's sufficient for an agent to understand inputs and outputs.

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?

Input schema covers 100% of parameters with descriptions, so baseline is 3. The description adds no significant parameter details beyond the schema, though it reiterates the auto-validation behavior for plantuml_code.

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 ('Generate') and resource ('PlantUML diagram') and clearly distinguishes from sibling tools like decode_plantuml/encode_plantuml by adding automatic syntax validation and error reporting.

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?

States the tool is for 'auto-fix workflows' and describes its typical use of generating diagrams with validation. It doesn't explicitly name alternatives, but the description implies when to use it versus other PlantUML utilities.

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 full behavioral burden. It discloses the core function but omits important details such as whether code is sent to external services, potential side effects, resource consumption, or safety implications, leaving the agent without adequate 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 a single sentence that front-loads the main action and output, with no redundant words or filler. Every word contributes to understanding the tool's purpose.

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 2-parameter tool with no output schema, the description adequately states the output type (HTML report) and content (visual indicators for issues and strengths). A slight gap is the lack of detail on how the report is returned or delivered, but overall it is sufficient for basic usage.

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?

Both parameters are fully documented in the schema with descriptions, providing 100% coverage. The description adds no additional parameter meaning beyond what the schema already specifies, 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 the tool's action (analyze code) and output (generate a detailed HTML report with visual indicators), distinguishing it from sibling analysis tools by specifying the report format and content focus.

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 visual HTML report is needed, but it does not explicitly contrast with sibling tools like analyze_code or validate_code, nor does it mention when this tool should be avoided.

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 behavioral disclosure. It states the tool 'gets information', which implies read-only, but it does not explain what the response contains, whether the capabilities reflect the current environment, or any other behavioral details. This lack of context leaves the agent uncertain about the tool's output.

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, efficiently worded sentence that conveys the essential purpose without any fluff or repetition. It is perfectly concise and front-loaded.

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 tool's simplicity with no parameters and no output schema, the description is minimally adequate. However, it lacks any guidance on what the returned information looks like or how to interpret 'execution capabilities', and does not provide context on how this fits into a larger workflow (e.g., checking capabilities before executing code).

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 is nothing to explain beyond the schema. Per the rubric, a baseline of 4 is appropriate. The description adds context about the purpose but does not need to elaborate on parameter semantics.

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 'Get' and clearly identifies the resource: 'information about supported languages and execution capabilities'. This makes the tool's purpose straightforward, though it doesn't explicitly contrast with sibling tools like execute_code.

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 usage context is implied: one would call this tool when they need to know which languages and execution capabilities are available. However, there is no explicit guidance on when to use this over alternatives, nor any mention of prerequisites or 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 provided, so the description must carry the burden of behavioral disclosure. It states the tool retrieves code samples from 'official Microsoft Learn documentation' and emphasizes 'LATEST OFFICIAL' snippets, which adds source context. However, it does not explain the return format, pagination, rate limits, or how to handle cases with no results, leaving some behavioral aspects undisclosed.

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 well-organized with clear sections for purpose, usage, and pattern. It front-loads the core function and uses bullet points for readability. Minor redundancy like the duplicated language list and the phrase 'empower coding capabilities' add slight fluff, but the overall structure keeps it efficient.

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 search tool with only two parameters and no output schema, the description provides sufficient context: what it does, when to use it, and how parameters work. It lacks explicit mention of result format or error behavior, but given the tool's simplicity, the coverage is adequate.

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 query and language parameters fully described. The description's 'Usage Pattern' section adds a note on using descriptive queries or SDK/class/method names, but this largely mirrors the schema. The eligible language values are duplicated from the schema, adding no new semantic information.

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: 'Search for code snippets and examples in official Microsoft Learn documentation.' It specifies the resource (Microsoft Learn) and the purpose (retrieving code samples for Microsoft/Azure products), which distinguishes it from sibling tools like microsoft_docs_search that likely search broader documentation.

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 a dedicated 'When to Use This Tool' section with concrete scenarios: 'When you are going to provide sample Microsoft/Azure related code snippets in your answers' and 'When you are generating any Microsoft/Azure related code.' This gives clear usage context, though it does not explicitly mention alternatives or when not to use the 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 exist, so the description carries the burden. It mentions retrieving 'latest complete content', preserving markdown elements, and URL constraints. However, it doesn't address error handling, rate limits, or dynamic page behavior, leaving some transparency gaps.

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?

Well-structured with headers and front-loaded purpose. Some redundancy among bullet points in 'When to Use' (e.g., related use cases), but each section serves a purpose. Slightly verbose for a one-parameter tool.

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 simple single-parameter schema and absence of output schema, the description provides comprehensive context: output format, URL requirements, usage ordering, and exclusion criteria. It fully equips an agent to select and 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?

Schema coverage is 100% for the single URL parameter, but the description adds meaningful constraints: valid HTML from microsoft.com domain and binary files unsupported. This enhances schema semantics.

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 and converts Microsoft Learn documentation pages to markdown, naming specific technology areas (Azure, .NET, Microsoft 365). It distinguishes itself from sibling microsoft_docs_search by focusing on complete page retrieval rather than search.

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?

An explicit 'When to Use This Tool' section lists conditions, and 'Usage Pattern' directs to use after microsoft_docs_search. It also states unsupported binary URLs, providing clear 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 full burden and does an excellent job. It discloses return limits (up to 10 chunks), token constraints (max 500 tokens), content source (Microsoft Learn and other official sources), and output format (title, URL, excerpt). This is rich behavioral transparency beyond what any schema would show.

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 well-structured and front-loaded with purpose, followed by output specifics and a follow-up pattern. Every sentence adds value; the content is concise for the amount of useful information conveyed.

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 simple 1-parameter search tool with no output schema, the description is thorough. It explains what results look like, how many, their size, source, and how to proceed with a complementary tool, making it fully contextual for an agent.

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 has 100% coverage with a clear description of the query parameter. The tool description adds no additional parameter semantics beyond what the schema already states, 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 uses a specific verb ('Search') and resource ('official Microsoft/Azure documentation'), clearly stating what the tool does. It also distinguishes itself from sibling tools by noting it returns search results and identifies microsoft_docs_fetch as a complement for full detail.

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 gives explicit usage guidance: 'Always use this tool to quickly ground your answers' and provides an explicit alternative/follow-up: 'use microsoft_docs_fetch when high-value pages are identified.' This clearly states when to use this tool vs. the fetching alternative.

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 and no output schema, the description carries the full burden of behavioral disclosure, but it only states 'Find similar alternatives.' It does not mention network calls, result sorting, response structure, or side effects, providing essentially zero transparency about what the tool does beyond the bare action.

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 extremely short ('Find similar alternatives'), which is concise but to the point of under-specification. It lacks the essential details needed to be useful, so it is not appropriately sized; it is merely insufficient.

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 absence of an output schema and annotations, the tool's description should explain what 'alternatives' means, how results are computed, and what the response looks like. It does none of this, leaving the agent with only input schema knowledge and no understanding of the tool's actual behavior or output.

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 fully documents both parameters ('packages' as an array of package names, 'ignoreCache' as a bypass-cache flag), achieving 100% schema_description_coverage. The description adds no parameter-specific meaning beyond the schema, 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 'Find similar alternatives' is a generic verb phrase that restates the tool name without specifying the resource (npm packages) or the criteria for similarity. It does not distinguish itself from sibling tools like npmCompare or npmSearch, leaving the actual purpose ambiguous.

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?

No usage guidance is provided. There is no indication of when this tool should be used instead of npmCompare, npmSearch, or other npm analysis tools. The description lacks both explicit scenarios and exclusions, offering no direction for tool selection.

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 behavioral disclosure, but it reveals nothing about caching behavior, output format, data sources, or side effects. The existence of an 'ignoreCache' parameter hints at caching but the description doesn't address it, leaving the agent completely in the dark about tool 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 extremely short but under-specified rather than appropriately concise. It is a fragment that doesn't form a complete sentence or convey essential information, so it fails to serve as an effective summary.

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?

With no output schema and numerous sibling tools, the description is drastically incomplete. It doesn't explain what the tool returns, its scope, limitations, or how it relates to other npm analysis tools, making it nearly useless for an AI agent evaluating 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 input schema already describes both parameters (packages and ignoreCache) with 100% coverage, so the baseline is 3. The description adds no additional semantic meaning beyond what the schema provides, but it doesn't need to since the schema is sufficient.

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 'Changelog & release history' is a noun phrase that restates the tool's name without an action verb, making it more of a tautology than a clear purpose. It doesn't specify whether the tool retrieves, analyzes, or compares changelog data, and it fails to differentiate from sibling tools like npmVersions or npmPackageReadme.

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 no guidance on when to use this tool versus the many alternative npm analysis tools. There is no mention of use cases, prerequisites, exclusions, or alternative tools, leaving the agent without any contextual direction.

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 behavior. It only says 'compare multiple packages' without explaining whether this performs network requests, respects caching (though the parameter hints at it), or what the output format is. This is insufficient for a tool that likely fetches package data.

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 extremely concise with no verbose language. It is front-loaded and communicates the core purpose in a short phrase. However, it is under-specified, which is penalized in other dimensions, but as a standalone string it is efficient.

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, no annotations, and a moderate complexity input. The description is incomplete for a tool that presumably returns a comparison report; it does not explain what the output looks like, limitations, or which metrics are compared. Contextual completeness is low.

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 'packages' and 'ignoreCache' described. The description adds no additional meaning beyond the schema; it does not clarify how parameters influence the comparison. Baseline 3 is appropriate as the 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 states the verb 'compare' and the resource 'multiple packages', indicating a side-by-side comparison tool. It is distinct from sibling tools that analyze individual packages, but lacks specifics on what aspects are compared (e.g., size, score, maintainers), which would fully differentiate it.

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 gives no guidance on when to use this tool versus alternatives. It implies usage when comparing packages, but does not mention exclusions, alternatives, or prerequisites. Given many npm-related sibling tools, the lack of usage context is a notable gap.

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. 'Check deprecation status' implies a read-only operation but discloses no behavioral traits such as network usage, caching behavior, or output format. It stops short of even a minimal behavioral disclosure.

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 one-sentence description is efficient and front-loaded, but it's under-specified. It sacrifices necessary context for brevity, making it more of a terse summary than a properly calibrated description.

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?

Without an output schema, the description should explain what 'deprecation status' returns (e.g., boolean, message, deprecation date), but it doesn't. The tool is simple, yet this minimalism leaves critical ambiguity.

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% (both 'packages' and 'ignoreCache' have descriptions), so the baseline is 3. The description adds no additional parameter meaning, but the schema already documents the essentials.

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 'Check deprecation status' clearly identifies a verb and resource, and the specific focus on 'deprecation' distinguishes it from sibling tools like npmLatest or npmVersions. It's concise but lacks detail on what exactly is checked or returned.

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 no guidance on when to use this tool versus alternatives. There are no context hints, exclusions, or references to sibling tools, leaving the agent to infer usage solely from the name.

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 behavioral disclosure. It reveals nothing about whether the tool is read-only, whether it caches results, network usage, or what kind of analysis is performed. The phrase 'analysis' is too vague to indicate any 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 extremely brief (five words) but under-specifies the tool's functionality. It is not appropriately sized because it omits critical information, making it more under-specified than concise.

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?

With only two parameters, no output schema, and no annotations, the description should explain what the analysis returns and how it behaves. It provides no such detail, leaving the tool's purpose and output largely unclear even in 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?

The input schema has 100% coverage with descriptions for both parameters: 'packages' as 'Package names array' and 'ignoreCache' as 'Bypass cache'. The description adds no additional parameter semantics, so it meets the baseline for high 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 'Deps & devDeps analysis' indicates the tool relates to dependencies and devDependencies, but it lacks a specific verb or action (e.g., 'list', 'fetch', 'compare'). It provides a vague sense of purpose without distinguishing from the many sibling npm tools, though it is not a pure tautology.

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?

There is no guidance on when to use this tool versus alternatives like npmCompare or npmVersions. The description only states the general topic without any context, prerequisites, or 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, the description carries full behavioral disclosure burden, but it only states what is returned (latest version & changelog). It does not disclose caching behavior, rate limits, output format, or whether it makes network requests. This is a significant gap for a tool that depends on external data.

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 bare noun phrase, not a properly structured sentence. While it is short, it is under-specified to the point of being a fragment, similar to the 'Process' example. It does not capture the action or provide actionable guidance.

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 tool has only 2 parameters and no output schema or annotations, the description is too minimal to be complete. It omits details such as what a 'package name' is, how results are returned, and why one would use this tool. The description leaves too much to inference.

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 describes both parameters (packages array and ignoreCache boolean) with 100% coverage. The description adds no additional semantic value beyond what the schema provides, so it meets the baseline for schema-driven parameter understanding.

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 'Latest version & changelog' clearly conveys that the tool fetches the latest version and changelog for npm packages. It lacks an explicit verb like 'get' or 'retrieve,' but the resource and scope are evident, and it distinguishes itself from siblings like npmVersions and npmChangelogAnalysis.

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?

There is no guidance on when to use this tool versus alternatives. No mention of when to prefer npmLatest over npmVersions or npmChangelogAnalysis, nor any exclusions or prerequisites. The description provides no usage 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to indicate whether this is a read-only check, what inputs it expects (beyond schema), what output format it returns, or any side effects. The single phrase provides no 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?

While very short, this is under-specification rather than conciseness. The three-word description does not earn its place by conveying any useful information; it simply restates the tool's purpose in noun form.

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 3 parameters, a required array, and no output schema, yet the description provides no context about the expected behavior, parameter roles, or return value. It is completely inadequate for an agent to select and invoke this tool 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% with brief but present descriptions for packages, ignoreCache, and projectLicense. The tool description itself adds no meaning beyond the schema, but per the baseline for high coverage, a 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 'License compatibility check' is essentially a tautology of the tool name 'npmLicenseCompatibility'. It does not state a specific verb and resource, nor does it distinguish this tool from its many npm-related siblings like npmAlternatives or npmCompare.

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?

There is no guidance on when to use this tool versus alternatives. It does not say anything about checking licensing before using certain packages, comparing project vs dependency licenses, or any other usage 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 provided, so the description must disclose behavioral traits. It offers no information about return format, caching behavior, network calls, or any side effects. This is a significant gap for a tool that likely performs external queries.

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 two-word description is concise in word count but under-specified. It is not appropriately sized because it fails to convey essential functional information, making it more of a placeholder than a concise description.

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?

With no output schema, no annotations, and a merely titular description, the tool is contextually incomplete. The agent cannot determine return values, expected behavior, or appropriate usage scenarios, making the description completely inadequate.

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%: 'packages' is described as 'Package names array' and 'ignoreCache' as 'Bypass cache'. The description itself adds no parameter meaning, but the schema fully documents the parameters, 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 'Maintainers info' is a noun phrase that restates the tool name without any verb or action. It does not clarify what operation is performed (e.g., fetch, list, retrieve) and fails to distinguish the tool from sibling tools like npmMaintenance or npmScore.

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?

No guidance is provided on when to use this tool versus alternatives. The description gives no context, exclusions, or mention of sibling tools, leaving the agent without criteria for tool selection.

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 of disclosing behavior, but it only states a vague domain. It does not indicate whether the operation is read-only, what data it returns, whether it makes network requests, or any other behavioral traits. This is a significant gap for a tool that likely queries npm data.

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 under-specified—a single phrase that does not earn its place by providing critical information. While it is short, it is not effectively concise; it omits essential details and lacks any front-loaded actionable 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 tool with 2 parameters, no output schema, and no annotations, this description is severely inadequate. It does not explain what maintenance metrics are, how they are calculated, what result format to expect, or how this tool differs from the many related npm sibling tools. The agent cannot reliably invoke or interpret the tool's output.

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 descriptions for both parameters ('Package names array' and 'Bypass cache'), covering 100% of parameters. However, the tool description adds no extra meaning about how these parameters relate to analysis or what 'maintenance metrics' means. The schema descriptions are minimal, but enough for the baseline of 3.

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 'Maintenance metrics analysis' is a noun phrase rather than a clear verb+resource statement. It does not specify what the tool does (e.g., 'fetch', 'calculate', 'report') and is barely more informative than the tool name itself. It does not distinguish from sibling tools like npmQuality or npmRepoStats.

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 no guidance on when to use this tool versus alternatives such as npmScore, npmDeps, or npmQuality. There is no mention of intended scenarios, prerequisites, or exclusions. The lack of any usage context leaves the agent without direction.

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 full responsibility for behavioral disclosure. It mentions nothing about fetching behavior, caching, error handling, or output format, leaving the agent completely in the dark.

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 extremely short and under-specified. This is not conciseness but rather a failure to provide essential information.

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 large set of sibling npm tools and the lack of annotations or output schema, this description is grossly insufficient. It explains neither when to use the tool nor what to expect from it.

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 descriptions cover both parameters (packages and ignoreCache) with adequate descriptions, so the tool description doesn't need to add parameter details. 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?

The description is a noun phrase rather than a sentence with a verb, stating only the output ('Full README content') without specifying the action. It doesn't distinguish the tool from siblings like npmChangelogAnalysis or npmDeps.

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 no guidance on when to use this tool versus alternatives. No context about intended use cases or exclusions is given.

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 behavior. It only says 'Quality metrics analysis', which implies some read-only inspection but does not state what data is accessed, whether any side effects occur, how results are returned, or any prerequisites or limitations.

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?

At three words, the description is under-specified rather than concise. It does not front-load actionable information; it merely hints at the domain, making it insufficient for an agent to understand the tool's operation.

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?

With no output schema and no annotations, the description must compensate by explaining return values and behavior. It does neither, leaving the agent without key context such as what metrics are produced or how the analysis is performed.

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 descriptions for both parameters ('Package names array' and 'Bypass cache'), so schema coverage is 100%. The description adds no additional parameter context, but the schema already handles the semantics, yielding the baseline score of 3.

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 'Quality metrics analysis' is a vague noun phrase that largely restates the tool name 'npmQuality'. It lacks a specific verb and resource, and does not differentiate this tool from the many sibling npm analysis tools (e.g., npmScore, npmMaintenance, npmRepoStats).

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?

There is no guidance on when to use this tool versus alternatives. Given the extensive sibling list of npm-related analysis tools, the description provides no context for selection or exclusion, leaving the agent to guess.

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 behavioral disclosure. It only says 'Repository statistics' and does not explain what statistics are computed, whether the operation is read-only, if it makes network calls, how caching works, or what output format to expect.

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 under-specified rather than appropriately concise. A single vague phrase 'Repository statistics' does not earn its place; it provides no actionable information and is closer to a placeholder than a useful tool description.

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?

Despite having a simple two-parameter schema, the description is far from complete given the lack of annotations, output schema, and sibling differentiation. The agent cannot understand what the tool does, what it returns, or how to use it effectively, especially with 38 sibling tools covering similar npm analysis.

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 has high description coverage (100%) with 'Package names array' and 'Bypass cache' documented. Since schema coverage exceeds 80%, the baseline is 3, and the description adds no additional parameter meaning beyond what 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 'Repository statistics' is a noun phrase that paraphrases the tool name 'npmRepoStats' without stating a specific verb or resource. It does not clearly indicate what action the tool performs or what it returns, and it fails to distinguish among the many npm-related sibling 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 no guidance on when to use this tool versus alternatives like npmTrends, npmScore, or npmCompare. There is no context, exclusions, or mention of alternative tools, leaving the agent without criteria for tool selection.

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 bears full responsibility for disclosing behavior. It only says 'Consolidated package score' without explaining what data is fetched, whether the operation is read-only, how caching works, or any side effects. This is effectively no behavioral disclosure.

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 extremely short, but this is under-specification rather than conciseness. It lacks any detail that would help an agent understand the tool's purpose, return value, or usage context.

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 absence of annotations and output schema, and a description that only restates the tool's name, the description is severely incomplete. It does not explain what a 'score' consists of, how the input array is used, or what the agent should expect in response.

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 descriptions for both parameters ('Package names array' and 'Bypass cache'), so schema coverage is 100%. The description adds no additional meaning beyond the schema, earning the baseline score of 3.

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 'Consolidated package score' identifies the resource (npm packages) and concept (a score), but lacks a specific verb and does not clearly differentiate from sibling tools like npmQuality or npmMaintenance. It reads more as a noun phrase restating the tool name rather than a full explanation of what the tool does.

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?

No guidance is provided about when to use this tool versus alternatives. With numerous sibling tools covering specific npm aspects (e.g., npmVulnerabilities, npmMaintenance, npmQuality), the description gives no indication of when 'consolidated package score' would be preferred.

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?

There are no annotations, so the description carries the full burden of disclosing behavior. It only says 'Search NPM packages', which adds no behavioral detail beyond the tool name. It does not explain whether results include version metadata, whether it hits the live registry, how pagination or caching works (though the ignoreCache parameter hints at caching), or any rate limits.

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, concise sentence with no fluff. However, it is under-specified—it essentially restates the tool name with a verb. While concise, it sacrifices usefulness for brevity, providing minimal information about the tool's behavior or context.

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?

With no output schema and no annotations, the description needs to set expectations for what the tool returns, but it does not. It is unclear what fields are returned (does it return the package name, description, version, maintainers?). The description also fails to mention how it handles caching or what the 'limit' parameter truly impacts beyond 'Max results'. The tool is simple, but the description is incomplete for an agent trying 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?

The input schema has 100% parameter coverage with descriptions for query, limit, and ignoreCache. The description adds no extra semantic value, but the baseline of 3 applies because the schema does the heavy lifting. Parameters are reasonably self-explanatory.

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) and resource (NPM packages), fulfilling the basic requirement. However, it does not differentiate itself from sibling tools like npmLatest or npmVersions, which also relate to NPM package data. It is clear but lacks specificity about what kind of search (by name, metadata, etc.) or result scope.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling npm tools available (npmQuality, npmScore, npmTrends, etc.), the description gives no hint about what unique purpose npmSearch serves or when a user should prefer it. This is a clear gap.

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 must disclose behavior. The phrase 'Package & bundle size' reveals nothing about side effects, network access, caching, or return format, offering zero behavioral 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 a short noun phrase, but it is under-specified rather than appropriately concise. It lacks a complete sentence and does not effectively use the space to convey needed information.

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 absence of annotations and output schema, and the presence of a 2-parameter input schema, the description is gravely incomplete. It does not explain what the tool does with packages, how size is determined, or what the response contains.

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 both parameters described ('Package names array' and 'Bypass cache'). The tool description adds no additional meaning to the parameters, so the baseline score 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 'Package & bundle size' essentially restates the tool name (npmSize) without an action verb. It fails to indicate whether the tool retrieves, compares, or analyzes size information, making it largely tautological.

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 no guidance on when to use this tool relative to the many sibling npm tools. No use cases, prerequisites, or 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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It only says 'Download trends & popularity' without clarifying what 'download' entails (e.g., output format, network requests, caching behavior, or whether it's a safe read operation). This is a significant omission.

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 very short (four words), but this is under-specification rather than effective conciseness. It lacks substance needed for the agent to understand the tool's scope, making it less useful without further 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 the complexity of the npm ecosystem and many sibling tools, the description is incomplete. It doesn't explain what 'trends' data looks like, what output to expect, or how it relates to other npm tools. No output schema exists, so the description should compensate but doesn't.

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?

All three parameters have descriptions in the schema ('Period', 'Package names array', 'Bypass cache') with 100% coverage. The description adds no additional parameter context, but the baseline of 3 is appropriate since the schema itself is sufficient.

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 'Download trends & popularity' identifies a verb and resource, but it is vague about what exactly 'trends' refers to (e.g., download counts over time?) and doesn't distinguish this tool from sibling tools like npmScore or npmVersions. It conveys a general purpose but lacks specificity.

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?

No usage guidance is provided. The description doesn't explain when to use npmTrends instead of alternatives like npmCompare, npmSearch, or npmScore, nor does it state any prerequisites or limitations.

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 full responsibility for disclosing behavior. It provides no information about what the tool does beyond a vague label, no return format, side effects, or limitations. The agent would be completely in the dark about runtime 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 extremely short ('TS types availability'), but this is under-specification rather than conciseness. It lacks a complete sentence and essential information, so it doesn't earn its place as a meaningful explanation.

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 tool has no output schema and no annotations, the description should explain the return value and behavior. It does neither. The schema covers parameters, but the overall tool remains incomplete for an agent to reliably invoke it.

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 has 100% description coverage for both parameters ('Package names array' and 'Bypass cache'), so the description doesn't need to add parameter details. However, the description itself adds zero value to parameter understanding, making the baseline score of 3 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 'TS types availability' is a fragment without a verb, making it unclear what action the tool performs. It vaguely hints at TypeScript type information but fails to specify whether it checks existence, fetches definitions, or analyzes something. It also doesn't distinguish itself from sibling tools like npmDeps or npmSearch.

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?

No usage context is provided. The description doesn't indicate when to use this tool versus alternatives among the many npm-related siblings. There are no explicit or implicit guidelines for selecting it.

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 behavioral disclosure. It does not mention that this is a read-only operation, that it may hit the npm registry, or that it uses caching (despite the ignoreCache parameter). There is zero behavioral 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?

The description is under-specified, consisting of a short fragment that does not earn its place. While brevity is generally good, this is too terse to communicate essential information, so it falls short of effective conciseness.

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 annotations and no output schema, the description is inadequate. It does not explain the return format, clarify what 'available versions' means, or describe any behavior beyond the tool name. For a tool with parameters and a defined purpose, this is a significant completeness 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 description coverage is 100%: the input schema already documents 'packages' as 'Package names array' and 'ignoreCache' as 'Bypass cache'. The description adds no additional parameter meaning, but the baseline of 3 applies because the schema already covers parameter semantics.

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 'Available versions list' is a noun phrase rather than a clear verb + resource statement. It roughly restates the tool name npmVersions without specifying that it lists versions for npm packages or providing any action verb, making it essentially a tautology.

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?

No guidance is provided about when to use this tool versus its many siblings (e.g., npmLatest, npmDeps, npmCompare). The description is only five words and gives no context, prerequisites, or 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 must bear the full burden of behavioral disclosure. 'Security analysis' says nothing about whether the tool is read-only, what external resources it accesses, side effects, authentication needs, or return value structure. This is critically uninformative.

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 under-specified rather than concise. It consists of only two words, providing no structure, headings, or useful detail. A concise description should still contain essential information to guide the agent; this one does not.

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 absence of annotations and output schema, the description should clearly explain what the tool returns and any behavioral effects. It does neither. The tool appears to be a security analysis utility, but no behavior or outcome is documented, making it completely inadequate for an AI agent.

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 'packages' and 'ignoreCache' already described. The description adds no extra meaning to the parameters. Baseline score of 3 is appropriate because the schema handles the parameter documentation, but the description offers no enhancements.

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 'Security analysis' is extremely vague and does not state what the tool does with npm packages. It lacks a clear verb and resource, and it fails to distinguish itself from sibling tools like check_security or npmQuality. It is barely more informative than the tool name itself.

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?

There is no guidance on when to use this tool versus alternatives. The description does not mention prerequisites, context, or exclusions, and it does not reference sibling tools. A two-word description provides no usability 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?

With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions 'sandbox' which implies isolation, but it does not explain return values, error handling, timeout behavior, or side effects. For a code execution tool, this is a significant 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 a single, focused sentence that immediately states the tool's purpose. There is no redundant wording; it is 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 code execution tool with four parameters, no output schema, and no annotations, a one-sentence description is insufficient. It lacks information about return behavior, error handling, and parameter details, leaving the agent with minimal context beyond the tool's name.

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 only 25% (just 'code'). The description clarifies that 'requirements' are PEP 723 style, but it does not add meaning for 'context' or 'timeout'. This partially compensates for the coverage gap but leaves most parameters underspecified.

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 ('Run'), the resource ('Python'), and the environment ('Pyodide sandbox'), and mentions optional PEP 723 requirements. However, it does not explicitly distinguish this from sibling tools like execute_code or execute_code_with_variables, so it falls short of a 5.

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 offers no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or when to prefer a sibling tool. This is a clear absence of usage direction.

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 behavioral disclosure. It does reveal that the tool retrieves up-to-date docs and imposes a 3-call limit, but it does not describe the return format, error handling, or any side effects. This is partial transparency but not comprehensive, earning a middle 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 concise and front-loaded. The first sentence states the purpose, the second gives the crucial prerequisite, and the third sets a usage restriction. Every sentence earns its place, with no filler or redundant information.

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 output schema and no annotations, the description provides enough to begin using it but does not specify what the returned documentation looks like or how errors are communicated. The prerequisite and call limit are useful, but more detail about return values and failure modes would make it more 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 baseline is 3. The description reinforces the need to obtain libraryId from resolve-library-id, but this information is also present in the schema. The query parameter examples are helpful but already in the schema. No significant additional semantic value is provided.

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: retrieving and querying up-to-date documentation and code examples from Context7 for any library or framework. It uses specific verbs ('Retrieves and queries') and a specific resource ('documentation and code examples from Context7'), which distinguishes it from sibling tools like microsoft_docs_search or npmSearch.

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 explicit usage guidelines: it requires calling resolve-library-id first unless the user supplies an ID in a specific format, and it sets a hard limit of 3 calls per question with a fallback instruction. However, it does not mention alternative tools or when not to use this tool, so it misses the 'alternatives' part of the rubric.

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 burden. It discloses the selection criteria (name similarity, description relevance, documentation coverage, reputation, benchmark score), the response format, handling of multiple/no matches, and an explicit rate limit of 3 calls per question.

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 longer than average but well-structured with sections (Selection Process, Response Format, IMPORTANT). It front-loads the MUST requirement and provides necessary procedural details, with each sentence serving a purpose. Slightly verbose but appropriately sized for the tool's complexity.

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?

With no output schema, the description explains the response format (clearly marked section, explanation, acknowledgment, suggestions). It also covers edge cases like no matches and ambiguous queries, plus the call limit, making it fully complete for a 2-param 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 description coverage is 100% and both parameters are clearly documented in the schema. The description reinforces their purpose ('Analyze the query...') but does not add new semantic details beyond what the schema already provides, so 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 begins with 'Resolves a package/product name to a Context7-compatible library ID and returns matching libraries,' which precisely states the action and resource. It also distinguishes from sibling tools by explicitly requiring it before 'query-docs'.

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?

States 'You MUST call this function before query-docs' and clarifies the exception when the user provides a library ID. Also provides guidance for ambiguous queries and a 3-call limit, giving clear when-to-use instructions.

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?

The description discloses a key behavioral trait—non-execution of code—which addresses the primary safety concern. However, with no annotations and no output schema, it does not describe return values, error handling, or potential limitations beyond the language support already in the 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 that is front-loaded with the action 'Validate code' and includes necessary qualifiers like 'for security and syntax issues' and 'without executing it'. 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?

The tool itself is simple with two well-specified parameters, but the description omits any mention of return value or output format, which is significant given the absence of an output schema. It also lacks guidance on potential false positives or coverage limitations.

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 both parameters ('language' with enum values and 'code' as a string), and the description adds no additional parameter-level meaning. Baseline 3 applies due to 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 uses a specific verb 'Validate' with a clear resource 'code' and defines the scope (security and syntax issues) while explicitly stating 'without executing it'. This distinguishes it from siblings like execute_code and check_security.

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 clearly implies when to use this tool: to validate code for issues without running it. The phrase 'without executing it' provides clear context as a safe alternative to execution tools, though it does not explicitly name alternatives or exclusions.

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