xpay✦ DevTools Collection

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 offers minimal detail. It mentions returning a 'structured analysis' but does not clarify if the tool executes code (relevant given execute_code siblings), whether it is read-only, rate limits, or the specific format/structure of returned 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 consists of two efficient sentences with zero redundancy. The first sentence front-loads the core functionality (what is analyzed), and the second sentence explains the return value. Every word serves a 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?

Given the lack of an output schema, the description minimally addresses the return value ('structured analysis with issues and strengths') but lacks detail about the analysis structure. For a tool with only two well-documented parameters and many specialized siblings, the description is adequate but has significant gaps regarding output format and differentiation from alternatives.

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 (code and filename), including the detail that filename is used for language detection. The description adds no additional parameter context, but with complete schema coverage, no compensation is needed, meeting the baseline expectation.

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 analyzes code for security issues, errors, deceptive patterns, and placeholders using specific verbs and resources. However, it fails to distinguish this comprehensive tool from specialized siblings like check_security, check_deceptive_patterns, and check_placeholders, leaving ambiguity about which tool to use.

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 numerous specialized alternatives (check_security, analyze_patterns, etc.). It mentions the return value but does not address prerequisites, input constraints, or selection criteria for this comprehensive analyzer over focused tools.

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 disclosure burden. It adds valuable context about output characteristics ('confidence levels and implementation details') but omits other behavioral traits such as execution time, supported languages, or whether the analysis is performed locally versus remotely.

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 tightly constructed sentences with zero waste. The first establishes scope (GoF patterns), the second specifies detection targets (Singleton, Factory, etc.) and output characteristics. Information is front-loaded and every clause 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?

Given the tool has only 2 well-documented parameters and no output schema, the description adequately compensates by describing return value characteristics ('confidence levels and implementation details'). It appropriately addresses the tool's moderate complexity, though it could enhance completeness by mentioning supported programming languages or file size 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?

Schema description coverage is 100%, with both 'code' and 'filename' parameters fully documented in the schema. The description does not add parameter-specific semantics beyond what the schema provides, but the baseline score of 3 is appropriate given the complete schema coverage eliminates the need for descriptive compensation.

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 specific verbs ('Focused analysis', 'Detects') and clearly identifies the resource ('Gang of Four (GoF) design patterns'). It effectively distinguishes from siblings like 'analyze_code' and 'analyze_patterns' by explicitly scoping to GoF patterns specifically, and differentiates from 'check_deceptive_patterns' by focusing on classic/valid patterns rather than anti-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 through specificity ('GoF design patterns') suggesting use when seeking classic pattern detection, but lacks explicit guidance on when to prefer this over 'analyze_patterns' or 'analyze_code'. No explicit 'when not to use' or alternative recommendations 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 provided, the description carries the full burden of behavioral disclosure. It mentions the tool 'provides actionable suggestions' and detects 'inconsistencies', but fails to disclose whether the operation is read-only, if there are rate limits, or what the output format looks like (crucial given no output schema exists).

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 consists of two efficient sentences with no filler content. It front-loads the core action ('Analyze code') and immediately qualifies the scope, making every word earn 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?

While the input schema is fully described, the tool lacks an output schema and annotations. The description only vaguely mentions 'actionable suggestions' without clarifying return structure, format, or richness of analysis, leaving gaps in the agent's ability to predict the tool's utility.

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%, establishing a baseline of 3. The description mentions the three pattern levels (architectural, design, implementation) which align with the 'level' enum, but this largely mirrors the schema's own detailed descriptions without adding syntax guidance or examples beyond the structured data.

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 analyzes code for architectural, design, and implementation patterns using specific verbs ('analyze', 'detects'). However, it does not explicitly differentiate from siblings like 'analyze_design_patterns' or 'analyze_code', leaving ambiguity about which tool to select for overlapping use cases.

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 like 'analyze_code' or 'analyze_design_patterns'. The description lacks explicit when-to-use/when-not-to-use conditions or prerequisites (e.g., minimum code size, language support).

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. It successfully defines what constitutes 'deceptive patterns' through examples, but does not disclose whether the operation is read-only, what format findings take, or behavior when no patterns are found.

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 single sentence is efficiently front-loaded with the action verb and uses a high-value parenthetical to provide concrete examples. No words are wasted; every element 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?

Given the simple 2-parameter schema with complete coverage, the description adequately explains the tool's purpose. However, lacking an output schema, it could be improved by briefly describing what the tool returns (e.g., list of findings, locations, severity).

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 ('The source code to check', 'The filename'), so the baseline is 3. The description implies the code parameter is the inspection target but does not add syntax constraints, format requirements, or semantic details beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Check') with a well-defined resource ('code patterns that hide errors') and provides concrete examples ('empty catches, silent failures') that clearly distinguish it from sibling tools like analyze_code, check_security, and analyze_design_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?

While the specific examples imply when to use this tool (when suspecting error-hiding patterns), there are no explicit when-to-use guidelines, prerequisites, or named alternatives to guide selection over similar analysis tools like analyze_code.

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 disclosure burden. It defines the scope of detection (what gets checked) but lacks information about return format, whether findings include line numbers, severity levels, or if the operation is strictly read-only.

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?

Single sentence with zero waste. Front-loaded with the action verb 'Check' followed by a comprehensive list of detection targets. 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?

Given the simple 2-parameter schema and lack of output schema, the description adequately covers the tool's function but leaves gaps regarding return value structure and analysis depth. For a detection tool with no output schema, mentioning the return format would improve completeness.

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 source code to check', 'The filename'), establishing baseline 3. The description does not add parameter semantics beyond the schema, such as whether filename affects the analysis logic or is just for context.

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 specific detection targets (placeholder code, dummy data, TODO/FIXME comments, incomplete implementations) using concrete nouns. While it doesn't explicitly name sibling tools, the specificity implicitly distinguishes it from generic 'analyze_code' or security-focused 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?

No guidance provided on when to use this tool versus alternatives like 'analyze_code' or 'check_deceptive_patterns'. No mention of prerequisites (e.g., whether code should be syntactically valid first) or when-not-to-use conditions.

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 disclosure burden but omits critical behavioral traits: it does not confirm whether this performs static analysis (safe) or executes code (dangerous), nor does it describe the return format (findings list, severity scores, etc.). The 'etc.' qualifier leaves scope undefined.

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?

Single sentence of 9 words plus clarifying examples. Every element serves a purpose: verb establishes action, 'only' establishes scope restriction, examples specify vulnerability classes. No redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a 2-parameter tool with 100% schema coverage, clearly establishing analytical scope. However, absent output schema and annotations, the description should have disclosed output format or safety characteristics to be fully 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% ('The source code to check', 'The filename'), establishing baseline 3. The description adds no supplementary parameter semantics (e.g., expected file extensions, code size limits, encoding requirements), relying entirely on the schema documentation.

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?

Specific verb 'Check' with clear resource 'code' and scope 'security vulnerabilities only'. The parenthetical examples (hardcoded secrets, SQL injection, XSS) precisely define the security domain, effectively distinguishing it from sibling tools like analyze_code (general) and check_deceptive_patterns (UI/UX 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 word 'only' implies restricted usage to security concerns, providing implicit guidance. However, it lacks explicit when-to-use comparisons or named alternatives (e.g., 'use analyze_code for general quality checks'), forcing the agent to infer boundaries from the examples 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?

No annotations are provided, so the description carries the full burden. It explains the transformation (decoding) but omits error behavior (what happens with malformed input?), return format details, or whether this is a pure/idempotent operation.

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?

Single sentence with zero waste. Front-loaded with the action verb and immediately clarifies the source-to-target transformation. Appropriate length for a single-parameter utility 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?

Adequate for a simple one-parameter tool with no output schema. The description establishes the basic contract clearly, though explicitly stating the return value format (decoded string) would strengthen agent confidence when handling the 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?

With 100% schema description coverage, the schema already fully documents the 'encoded_string' parameter. The description provides baseline context but does not add parameter-specific details such as expected encoding format (base64/deflate) or validation constraints.

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 clear resources ('encoded PlantUML string' → 'PlantUML code'). It effectively distinguishes from sibling tool 'encode_plantuml' through inverse verb choice and establishes the exact transformation performed.

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?

Usage is implied by the function description (use when you need to decode), but there is no explicit guidance on when to prefer this over alternatives, error recovery strategies, or the specific scenario (e.g., extracting source from PlantUML URLs).

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. While it mentions 'URL usage' hinting at the output format, it fails to disclose the encoding algorithm used (deflate + specific encoding), output structure, or whether the operation is idempotent.

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 single sentence is efficient and front-loaded with the essential verb and resource. However, given the lack of annotations and output schema, it borders on underspecified rather than optimally 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?

For a single-parameter tool, the description is minimally adequate. However, it omits important context given no output schema exists: the return value format (encoded string), expected character set, and relationship to the decode operation.

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 the parameter 'plantuml_code' fully documented. The description adds minimal semantic value beyond the schema, only reinforcing that the code is for encoding. Baseline 3 is appropriate when schema documentation 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 clearly states the action (encode), the resource (PlantUML code), and the context (URL usage). It implicitly distinguishes from sibling 'decode_plantuml' through the opposite verb, though it doesn't explicitly contrast with 'generate_plantuml_diagram'.

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 provided on when to use this tool versus alternatives like 'generate_plantuml_diagram' or 'decode_plantuml'. No prerequisites or conditions 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions 'securely' and 'security measures,' it fails to specify sandbox restrictions (filesystem access, process spawning), what 'comprehensive error handling' entails, or the output format (stdout/stderr/exit codes). For a high-risk 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 sentence with the key verb and resource front-loaded. Minor redundancy exists between 'securely' and 'security measures,' but it avoids excessive verbosity while conveying the core function.

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 this is a 6-parameter arbitrary code execution tool with no output schema and no annotations, the description is insufficient. It lacks critical context about the execution environment, return value structure, and side effects that agents need to safely invoke this 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%, so the baseline is 3. The description mentions 'JavaScript or Python' which aligns with the language enum, and 'securely' hints at the sandboxing context for `enableNetworking`, but adds no syntax details, examples, or constraints 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 clearly states the action (execute) and resource (JavaScript or Python code), specifying the exact languages supported via the enum. However, it fails to distinguish from sibling `execute_code_with_variables` regarding variable support or from `python_execute` regarding when to prefer one over the other.

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 siblings like `python_execute` or `execute_code_with_variables`. No prerequisites are mentioned (e.g., whether certain imports are pre-installed or if specific syntax is required).

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 disclosure burden. For a code execution tool, it critically omits safety context (sandboxing, side effects, persistence), error handling behavior, and the nature of returned output. The schema reveals constraints (timeout, memoryLimit, enableNetworking) but the description adds no behavioral context beyond the basic execution statement.

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?

Single sentence that is appropriately front-loaded with the primary action. Efficient length with no redundant words, though the density trades off against missing safety and usage guidance that would necessitate additional sentences.

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?

Inadequate for a 7-parameter code execution tool lacking both annotations and output schema. The description omits critical operational context such as security implications, output format, error handling, and resource constraints that are visible in the schema but not contextualized in prose.

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?

With 100% schema description coverage, the baseline is appropriately 3. The description mentions 'key-value pairs' which aligns with the 'variables' parameter, but this largely restates information already detailed in the schema property descriptions. No additional semantic value added for the other 6 parameters.

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 core function (execute JavaScript/Python code) and identifies the key differentiating feature (dynamic input variables as key-value pairs). However, it fails to explicitly distinguish this tool from the sibling 'execute_code' tool, which is a significant omission given the sibling list.

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 provided on when to use this tool versus siblings like 'execute_code' or 'python_execute'. The description does not clarify prerequisites, safety considerations, or selection criteria for this specific variant.

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 successfully discloses key behaviors: automatic syntax validation, bifurcated return paths (image URLs for valid vs error details for invalid), and optional local file system side effects. It does not mention rate limits or authentication requirements, but covers the primary 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 well-structured sentences with zero waste. The first sentence covers generation, validation, and return behavior; the second covers the optional file saving. Information is front-loaded and every clause 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?

Given the absence of an output schema, the description appropriately explains return values (embeddable image URLs or structured error details). It covers the optional file persistence behavior. It omits mentioning the PLANTUML_ALLOWED_DIRS environment variable restriction, though this is documented in the parameter schema.

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%, establishing a baseline of 3. The description adds value by explaining the validation behavior (relating to plantuml_code), the nature of output (embeddable URLs relating to format), and the file saving capability (relating to output_path), providing semantic context beyond the structural schema definitions.

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 specific verbs ('Generate', 'validation', 'reporting') and clearly identifies the resource (PlantUML diagram). It distinguishes from siblings like encode_plantuml/decode_plantuml by emphasizing diagram generation, image URLs, and file saving capabilities rather than text encoding operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context for when to use the tool ('for auto-fix workflows') and distinguishes it from alternatives via return type descriptions (embeddable URLs vs structured errors). While it doesn't explicitly name sibling alternatives, the specific mention of validation and error reporting workflows helps identify appropriate use cases.

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 successfully discloses the output format (HTML with visual indicators for issues/strengths) but lacks safety-critical information such as whether the operation is read-only, potential side effects, or rate limiting considerations.

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 consists of a single, efficient sentence with no redundant or filler words. It front-loads the core action ('Analyze code') immediately followed by the specific output ('detailed HTML report'), making it appropriately sized and 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?

Given the tool's simplicity (two primitive parameters, no output schema), the description adequately covers the primary function. However, it could be strengthened by clarifying whether the HTML is returned as a string or saved to disk, and by addressing the crowded sibling tool space to aid selection.

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 ('code' and 'filename'), establishing a baseline score of 3. The description does not add additional parameter semantics (such as filename format expectations or code size limits), but none are required given the complete schema documentation.

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 analyzes code and produces an HTML report with visual indicators, providing specific verb-resource combinations. However, it does not explicitly differentiate from the sibling 'analyze_code' tool, leaving ambiguity about why to choose this over the simpler analysis option.

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 the numerous sibling analysis tools (analyze_code, analyze_patterns, check_security, etc.). While the HTML output format implies use cases requiring visual reports, there are no explicit when-to-use or when-not-to-use statements.

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

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

With no annotations provided, the description carries the full burden. It discloses the return value domain (languages and capabilities) but omits safety characteristics (read-only status), caching behavior, response format structure, or rate limiting constraints expected for a discovery endpoint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no redundant words. Information is front-loaded and appropriately sized for a simple discovery tool with no parameters.

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 low complexity (zero parameters) and lack of output schema, the description provides minimal viable context about return values. However, it should ideally specify the return format or structure since no output schema exists to document 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 tool has zero parameters and 100% schema coverage. As per the baseline rule for zero-parameter tools, this earns a 4. No additional parameter semantics are needed or 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 uses clear verb 'Get information' and specific resources 'supported languages and execution capabilities', distinguishing it from sibling execution/analysis tools. However, it doesn't explicitly contrast with tools like 'execute_code' or 'python_execute' to clarify this is metadata-only.

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 when/when-not guidance is provided, but usage is implied by the nature of the tool—you would call this before execution tools to discover capabilities. It lacks explicit guidance like 'Call this before execute_code to verify supported languages'.

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 disclosure burden. It successfully identifies the data source ('official Microsoft Learn documentation') and emphasizes 'LATEST OFFICIAL' content reliability, but lacks operational details such as result quantity limits, pagination behavior, or response format structure.

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 clear Markdown headers separating purpose, usage conditions, and usage patterns. Slightly verbose in the opening paragraph ('empower coding capabilities' and 'related coding tasks' are redundant), but efficiently lists the language filter options and maintains logical flow.

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 2-parameter search tool without output schema or annotations, the description adequately covers the search domain (Microsoft Learn), return type (code samples), and filtering capabilities. Minor gap in not describing the result structure or count, but sufficient for tool selection.

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%, establishing a baseline of 3. The description repeats the language enum values and query examples that are already comprehensively documented in the schema properties, adding minimal new semantic context beyond emphasizing that SDK/class/method names are valid inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Search') and resource ('code snippets and examples in official Microsoft Learn documentation'), clearly distinguishing it from sibling tools like microsoft_docs_search (general documentation) by focusing specifically on executable code samples and Azure/Microsoft-specific contexts.

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?

Contains an explicit '## When to Use This Tool' section with two specific trigger conditions: providing sample snippets and generating Microsoft/Azure code. This clearly signals when to select this tool over general documentation or analysis siblings.

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

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

With no annotations provided, the description carries the full burden. It discloses domain restrictions ('microsoft.com domain'), unsupported formats ('Binary files...are not supported'), output structure ('markdown with headings, code blocks'), and temporal behavior ('retrieves the latest complete content'). Minor gap: does not mention error handling behavior or authentication requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Excellent structure with clear hierarchical headers (When to Use, Usage Pattern, URL Requirements, Output Format). Front-loaded with core purpose. Every sentence conveys distinct information; no redundancy with the schema or tautology. Appropriate length for the 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?

For a single-parameter fetch tool without output schema or annotations, the description is comprehensive. It compensates for missing output schema by detailing the markdown output format, explains the relationship to sibling tools, and covers input validation requirements. No critical gaps remain for agent operation.

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?

While the schema has 100% coverage (baseline 3), the description adds significant semantic constraints beyond the schema's basic 'URL of the Microsoft documentation page'. The 'URL Requirements' section adds validation rules (must be HTML, must be microsoft.com domain, no binary files) that clarify what constitutes a valid input.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb-resource combination ('Fetch and convert a Microsoft Learn documentation webpage to markdown format') and explicitly lists the scope (Azure, .NET, Microsoft 365). It clearly distinguishes from the sibling 'microsoft_docs_search' tool by contrasting 'overview' vs 'complete picture' and 'search results' vs 'full content'.

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?

Contains an explicit 'When to Use This Tool' section with five specific scenarios and a 'Usage Pattern' section that explicitly names the sibling tool ('Use this tool AFTER microsoft_docs_search') and describes the orchestration pattern. This provides clear when/when-not guidance.

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

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

With no annotations provided, the description carries full behavioral disclosure burden. It successfully specifies return volume ('up to 10 chunks'), size constraints ('max 500 tokens'), data sources ('Microsoft Learn'), and result structure ('title, URL, and self-contained content excerpt'). Lacks rate limit or caching behavior details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two well-structured paragraphs with zero waste. The first sentence establishes core functionality and return format; the second section explicitly defines the follow-up pattern. Every sentence conveys unique information not present in structured fields.

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 lacking an output schema, the description comprehensively explains return values (chunks, tokens, metadata). For a single-parameter search tool, it adequately covers operational context, though it could mention error states (no results found) or authentication requirements.

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 has 100% description coverage ('a query or topic about Microsoft/Azure products...'), establishing a baseline of 3. The description implies the query parameter through phrases like 'user's query' but does not add syntactic guidance, validation rules, or example queries 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 uses specific verbs ('Search') and resources ('official Microsoft/Azure documentation') to clearly define the tool's function. It explicitly distinguishes itself from sibling tool microsoft_docs_fetch by positioning search as the discovery phase and fetch as the full-content retrieval phase.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('Always use this tool to quickly ground your answers in accurate, first-party Microsoft/Azure knowledge') and provides clear guidance on the follow-up workflow ('use microsoft_docs_fetch when high-value pages are identified'). The sibling relationship is clearly articulated.

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 provided, yet the description discloses nothing about behavioral traits: what 'similar' means algorithmically, what data sources are used, response format, or rate limiting. The description carries none of the required burden.

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 brief (three words), the description is under-specified rather than efficiently concise. It fails to front-load critical context needed to distinguish this tool from 25+ siblings.

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 rich sibling tool ecosystem (25+ tools including 20+ npm utilities), lack of output schema, and absence of annotations, the description is inadequate. It should clarify differentiation from npmSearch/npmCompare and explain the 'similarity' algorithm.

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?

With 100% schema description coverage ('Package names array', 'Bypass cache'), the schema carries the full load. The description adds no parameter context, but meets the baseline for high-coverage schemas.

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 nearly tautological with the tool name 'npmAlternatives' and fails to specify the domain (npm packages) or scope. It does not distinguish from sibling tools like npmSearch 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?

No guidance provided on when to use this tool versus alternatives like npmSearch or npmCompare. No mention of prerequisites, input format requirements, or caching behavior implications.

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, yet the description discloses no behavioral traits. It does not state the data source (npm registry), output format (raw markdown vs. parsed JSON), caching behavior beyond the parameter name, or what happens when changelogs are missing.

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 brief (3 words), it is underspecified rather than efficiently concise. It lacks sentence structure and fails the 'every sentence should earn its place' standard by providing insufficient information for tool selection.

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 explain return values and behavior. Instead, it provides only a fragmentary topic label. While the input schema is complete, the description inadequately covers the tool's functionality and 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 has 100% description coverage ('Package names array', 'Bypass cache'), establishing a baseline score of 3. The description itself adds no semantic information about parameters (e.g., that packages accepts up to 50 npm package names, or syntax details).

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' indicates the domain (changelog data) but lacks a specific verb describing what the tool does (fetch, analyze, retrieve?). It does not differentiate from sibling tools like npmVersions or npmLatest, leaving the agent uncertain about the specific value proposition.

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 guidelines are provided. There is no indication of when to use this tool versus the numerous sibling npm tools (npmVersions, npmLatest, npmPackageReadme, etc.), nor any prerequisites or constraints 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?

With no annotations provided, the description carries the full burden of behavioral disclosure but provides none. It does not explain comparison methodology, output format, rate limits, or cache behavior (despite the ignoreCache parameter implying caching exists).

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, this is under-specification masquerading as conciseness. No information is provided about comparison logic, output structure, or distinguishing features from sibling tools.

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 rich ecosystem of 25+ sibling npm analysis tools and the complexity of package comparison (likely involving multiple metrics), the description is inadequate. The agent cannot determine if this compares download trends, dependency trees, bundle sizes, or security posture.

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% ('Package names array' and 'Bypass cache'), so the schema adequately documents parameters. The description adds no parameter-specific context, but baseline 3 is appropriate when schema coverage 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 'Compare multiple packages' restates the tool name (npmCompare) with minimal elaboration. Given 25+ sibling npm tools (npmSize, npmDeps, npmTrends, etc.), it fails to specify what comparison criteria are used (size, popularity, maintenance, security?) or how this differs from specialized comparison alternatives.

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 provided on when to use this tool versus alternatives like npmAlternatives, npmSize, or npmTrends. No mention of prerequisites (e.g., whether packages must exist in registry) or when comparison is preferable to individual package analysis.

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 fails to disclose what deprecation information is returned (message, date, alternative package), how non-existent packages are handled, or whether this queries the npm registry in real-time.

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, it is brief but severely under-specified rather than efficiently concise. No sentence structure exists to evaluate for front-loading; the fragment provides minimal value per word.

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 should explain what deprecation data is returned. Given the tool accepts 50 packages and likely returns structured deprecation data, the description is 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% ('Package names array', 'Bypass cache'), so the baseline is 3. The description adds no semantic meaning beyond the schema, but also does not contradict it.

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' is tautological given the tool name 'npmDeprecated' and fails to explicitly identify the resource (npm packages). It does not distinguish this tool from siblings like npmMaintenance or npmVulnerabilities, which also check package health statuses.

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 provided on when to use this tool versus alternatives (e.g., npmMaintenance, npmVulnerabilities) or what constitutes a deprecation check versus other health checks. No prerequisites or conditions 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?

With no annotations provided, the description carries the full burden of behavioral disclosure but provides none. It does not explain what the 'analysis' entails (e.g., returning dependency trees, version ranges, conflict detection), what the cache behavior is, or whether this is a read-only registry query.

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 brief (3 words), it is under-specified rather than concise. The abbreviation 'Deps' assumes context, and the lack of a verb ('Performs analysis' vs just 'analysis') makes it scan poorly. Not front-loaded with actionable clarity.

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 no output schema to document return values, the description fails to explain what data structure or analysis results the tool returns. Given the crowded namespace of npm tools, the description is incomplete without specifying what unique information this tool provides (e.g., dependency tree vs. flat list vs. metrics).

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 ('Package names array', 'Bypass cache'), establishing a baseline of 3. The description adds no semantic context beyond the schema (e.g., expected package name format, cache bypass implications).

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 partially restates the tool name ('Deps') and uses the vague noun 'analysis' instead of a specific verb. It fails to distinguish this tool from siblings like npmVulnerabilities, npmLicenseCompatibility, or npmSize, which also perform 'analysis' on packages. It does not clarify whether it analyzes the dependencies OF the input packages or treats the inputs as dependencies to be analyzed.

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 provided on when to use this tool versus the 20+ sibling npm analysis tools. No mention of prerequisites (e.g., whether packages must be installed locally or are fetched from registry), nor when to set ignoreCache to true.

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 provided, so the description carries full behavioral burden. It mentions 'changelog' implying retrieval of changelog data, but fails to disclose caching behavior (despite having an ignoreCache parameter), return format, or registry source. Minimal behavioral context provided.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three-word description has zero fluff and is front-loaded with key concepts, but is so abbreviated it constitutes under-specification rather than effective conciseness. No structural issues beyond incompleteness.

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 rich ecosystem of sibling npm tools and lack of output schema, the description is inadequate. It fails to clarify the distinction between this tool and specialized siblings (npmChangelogAnalysis, npmVersions), leaving agents uncertain about tool selection.

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% ('Package names array', 'Bypass cache'), establishing a baseline of 3. The description adds no additional parameter semantics (e.g., npm package naming conventions, cache TTL details) 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?

Description 'Latest version & changelog' is a noun fragment without a verb (fetch? retrieve?), failing to specify the action performed. It partially distinguishes from siblings like npmVersions or npmChangelogAnalysis by combining both concepts, but the lack of a predicate makes the purpose vague.

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 provided on when to use this versus siblings like npmVersions (which likely returns all versions) or npmChangelogAnalysis (which likely analyzes changelogs). With over 20 npm-related siblings, the absence of selection criteria is a critical 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 carries the full burden of behavioral disclosure but provides none. It fails to mention caching behavior (despite the ignoreCache parameter implying it exists), what constitutes a compatibility conflict, whether the operation is read-only, or what the return format contains (list of conflicts? boolean? risk 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?

While brief (3 words), it is not appropriately structured—it is a sentence fragment rather than a front-loaded, information-dense statement. The extreme brevity reflects under-specification rather than effective conciseness; no constraints, return types, or critical behaviors are communicated.

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 legal complexity of license compatibility analysis and the presence of three parameters with specific semantics, the description is inadequate. It fails to explain the output format (critical for a 'check' tool), the license database source, or how to interpret compatibility results, leaving significant gaps for an agent attempting to 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?

With 100% schema description coverage, the baseline is 3. The description adds no supplemental meaning beyond the schema (e.g., it doesn't clarify that projectLicense expects an SPDX identifier, or that packages accepts npm package names with optional scopes). It relies entirely on the schema's minimal descriptions ('Package names array', 'Target license').

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' restates the tool name (tautology) without clarifying what 'compatibility' means (e.g., OSI-approved, SPDX-compliant, or compatible with a specific target license). It lacks specificity regarding the scope—whether it checks direct dependencies only or transitive ones—and fails to differentiate from sibling tools like npmVulnerabilities 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?

No guidance provided on when to use this tool versus alternatives (e.g., npmDeps for dependency analysis), prerequisites (e.g., valid package names), or expected inputs (e.g., SPDX license identifiers for projectLicense). The description offers no 'when-not-to-use' or workflow 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 fails to disclose behavioral traits such as caching semantics (despite the presence of an ignoreCache parameter), rate limits, authentication requirements, or data freshness guarantees.

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 represents under-specification rather than effective conciseness. While front-loaded, it fails to earn its place by providing insufficient actionable information about the tool's function.

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 complete schema coverage, the description is inadequate for a data retrieval tool lacking an output schema or annotations. It fails to explain what 'maintainers info' encompasses (emails, activity metrics, etc.) or how it differs from sibling npm analysis tools.

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' adequately documented in the schema itself. The description adds no parameter-specific context beyond what the schema provides, warranting 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?

The description 'Maintainers info' is essentially a tautology that restates the tool name without specifying the action performed (retrieve, fetch, list) or distinguishing it from similar siblings like npmMaintenance.

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 such as npmRepoStats or npmPackageReadme, nor are there any stated prerequisites or conditions for invocation.

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. While the ignoreCache parameter implies caching exists, the description doesn't explain the caching strategy, whether this is a read-only operation, what data sources are queried, or what the return format looks like.

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 (three words), but this constitutes under-specification rather than effective conciseness. The single fragment fails to earn its place by providing actionable context beyond the tool name.

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 many similar sibling tools, the description fails to compensate. It doesn't explain what maintenance metrics are returned, how they're calculated, or how results differ from npmQuality or npmRepoStats.

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 'Package names array' and 'Bypass cache' already documented in the schema. The description adds no additional parameter semantics, but baseline 3 is appropriate given 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 'Maintenance metrics analysis' is tautological and vague. It fails to specify what maintenance metrics are analyzed (e.g., commit frequency, issue response time), doesn't mention the resource (npm packages), and doesn't distinguish from siblings like npmMaintainers, 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?

No guidance provided on when to use this tool versus alternatives like npmMaintainers or npmRepoStats. No mention of prerequisites, rate limits, or when to set ignoreCache to true.

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, yet the description discloses no behavioral traits. It fails to mention network request behavior, the cache mechanism (despite the ignoreCache parameter), error handling for invalid packages, or that it returns raw markdown potentially containing large binary data or embedded images.

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 (3 words) and front-loaded, but this represents under-specification rather than efficient conciseness. While it contains no waste, it also fails to earn its place by conveying actionable information about 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 carries the full burden of explaining return values, format (markdown), size constraints, and multi-package behavior (array supports up to 50 items). It addresses none of these, leaving critical gaps for an AI agent attempting to invoke the 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?

The input schema has 100% description coverage ('Package names array' and 'Bypass cache'), establishing a baseline score of 3. The tool description 'Full README content' adds no semantic information about parameters, acceptable package name formats, or the implications of bypassing cache.

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 'Full README content' identifies the resource (README) but fails to specify the action (retrieve/fetch/get). It is a noun phrase describing output rather than a verb phrase describing function. It does not distinguish from sibling tools like npmSearch or npmRepoStats which also interact with package metadata.

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 provided on when to use this tool versus alternatives. Given the extensive sibling toolset (npmSearch, npmLatest, npmRepoStats, etc.), the description should specify when README retrieval is preferred over other package information queries, but it remains silent.

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, yet the description discloses no behavioral traits. It does not clarify whether this reads from a local cache (despite the ignoreCache parameter), what the return format is, rate limits, or whether the operation is read-only.

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 only three words, this represents under-specification rather than efficient conciseness. The single sentence fails to earn its place by providing actionable information about the tool's function.

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 analyzes npm package quality (a complex domain) and lacks an output schema, the description should explain what metrics are returned (e.g., npms.io scores, maintenance scores). It provides none of this context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with 'Package names array' and 'Bypass cache' documenting the two parameters. The description adds no additional semantic context about package name formats or cache behavior, warranting 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?

The description 'Quality metrics analysis' lacks specificity about what quality metrics are retrieved (e.g., maintainability, popularity, code coverage) and fails to distinguish from siblings like npmScore or npmMaintenance. It restates the concept implied by the tool name without clarifying the resource or 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 provided on when to use this tool versus alternatives like npmScore or npmMaintenance. No prerequisites or caching behavior is mentioned, despite the presence of an ignoreCache parameter.

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, yet the description discloses nothing about behavioral traits: what data source is queried, rate limits, whether 'repository' refers to GitHub or npm registry, what the cache mechanism entails, or what the return structure looks like.

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 two words, this is under-specification rather than effective conciseness. No information is front-loaded because no substantive information is present. The extreme brevity harms utility.

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 crowded namespace of npm-related sibling tools and lack of output schema, the description fails to establish unique value proposition or explain return values. It mentions 'statistics' but not which metrics distinguish it from specialized alternatives.

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% ('Package names array', 'Bypass cache'), so the baseline is 3. The description adds no additional parameter semantics (e.g., expected package name format, when to use ignoreCache).

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 tautological given the tool name npmRepoStats. It lacks a specific verb (fetch/retrieve/calculate) and fails to specify what statistics are returned (downloads, stars, forks?) or distinguish from siblings like npmTrends, npmSize, 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 provided on when to use this tool versus the 15+ sibling npm analysis tools (npmTrends, npmSize, npmMaintenance, etc.). No prerequisites or exclusion criteria mentioned.

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

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

No annotations are provided, so the description carries the full disclosure burden, yet it explains nothing about the score's composition (which factors are weighted), the data source (npm registry vs. npms.io), caching semantics despite the 'ignoreCache' parameter, or error handling for invalid package names.

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 only three words, the description is severely under-specified rather than efficiently concise. Given the absence of annotations and output schema, this brevity represents a failure to communicate essential context, not effective information density.

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 provided and no annotations, the description fails to compensate by explaining the return structure, score ranges, or what 'consolidated' means in the context of npm package evaluation. It leaves critical behavioral and contractual information completely undocumented.

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 ('Package names array' and 'Bypass cache'), so the baseline score applies. The description adds no additional semantics about parameter formatting or behavior, but the schema adequately documents the two parameters without further elaboration needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Consolidated package score' essentially restates the tool name ('npmScore') without specifying the action performed (retrieve, calculate, aggregate) or what 'consolidated' entails. It fails to distinguish this tool from siblings like 'npmQuality', 'npmTrends', or 'npmRepoStats' which likely return constituent metrics.

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 numerous sibling npm analysis tools (e.g., npmAlternatives, npmCompare, npmQuality). There are no stated prerequisites, exclusions, or conditions for optimal use.

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, and the description omits behavioral details: whether search covers package names, descriptions, or keywords; if it queries the live npm registry or a local index; rate limits; or cache behavior implications (only implied by the ignoreCache parameter).

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 three-word description is not verbose, but suffers from under-specification rather than genuine conciseness. With numerous sibling tools requiring differentiation, the single sentence does not earn its place 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?

Given the rich ecosystem of 20+ npm tools and lack of output schema, the description should explain the search scope, return format (package names vs. metadata), and relationship to specialized tools. It currently provides insufficient context for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage ('Search query', 'Max results', 'Bypass cache'), providing adequate documentation. The description adds no parameter-specific context, meeting the baseline expectation when schema coverage 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 states a clear verb ('Search') and resource ('NPM packages'), specifying the tool's core function. However, with over 20 npm-related sibling tools available, it fails to differentiate this general search from specialized alternatives like npmLatest or npmVersions.

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 the many specialized npm siblings (e.g., npmVersions for specific version lookups, npmLatest for newest releases). The agent has no criteria for selecting this over alternatives.

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 fails to mention caching behavior (despite having an ignoreCache parameter), data sources, rate limits, whether the tool performs live bundle analysis or registry lookups, or what the return format contains.

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 brief, the three-word phrase is underspecified rather than usefully concise. It lacks a complete sentence structure or actionable information. Every sentence should earn its place, but here there are no sentences—only a label that forces the agent to infer functionality from the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an npm package analysis tool with no output schema and no annotations, the description is inadequate. It omits critical domain context: whether it returns gzipped vs minified sizes, how it handles monorepos, or what constitutes a 'bundle' in this context. The description needs to compensate for the lack of output schema 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?

With 100% schema description coverage ('Package names array' and 'Bypass cache'), the structured schema adequately documents the parameters. The description adds no semantic value beyond the schema, but baseline 3 is appropriate when the schema carries the documentation burden.

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' is a noun phrase without a verb, failing to specify what action the tool performs (retrieve? calculate? analyze?). While it indicates the domain, it does not distinguish from siblings like npmCompare or npmDeps, nor does it clarify the scope of 'size' (install size vs bundle size vs minified size).

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 provided on when to use this tool versus alternatives. Given the extensive list of npm-related siblings (npmCompare, npmAlternatives, npmDeps, etc.), the description fails to specify selection criteria or prerequisites (e.g., when to check bundle size vs dependency count).

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, yet the description fails to disclose behavioral traits like rate limiting, data freshness, return format (time series vs aggregates), or the caching mechanism implied by the 'ignoreCache' parameter. The description carries the full burden of transparency and provides almost none.

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 only three words (a fragment, not a sentence) and is inappropriately brief for a tool with 3 parameters and numerous siblings. While not verbose, it fails the 'appropriately sized' criterion by lacking necessary 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 tool has 3 parameters, no output schema, and exists among many similar npm tools, the description is incomplete. It fails to explain what data structure is returned, what 'popularity' specifically measures (downloads, stars, dependents?), or how trends are calculated.

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?

With 100% schema description coverage ('Period', 'Package names array', 'Bypass cache'), the schema adequately documents parameters. The description adds no parameter semantics, but meets the baseline expectation when schema coverage is high.

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' indicates the tool deals with npm package download statistics and popularity metrics, but lacks a specific verb (retrieve/fetch/get) and fails to differentiate from siblings like npmCompare or npmScore. It is vague about whether 'Download' is an imperative or descriptive adjective.

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 provided on when to use this tool versus the 20+ sibling npm tools (e.g., npmCompare, npmSearch, npmScore). No mention of prerequisites, required setup, or specific use cases where this is preferred over alternatives.

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 burden for behavioral disclosure but provides none. It doesn't explain whether it checks @types organization, looks for bundled type definitions, returns boolean availability flags or package names, or details cache behavior beyond the bypass parameter.

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 maximally brief, but this brevity manifests as under-specification rather than efficient information density. No wasted words, yet insufficient content to earn a higher score for structural utility.

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 100% input schema coverage, the description is inadequate for the complexity of the npm/TypeScript types ecosystem. It fails to explain what 'availability' encompasses (DefinitelyTyped vs bundled types), output format, or behavior when types are missing, leaving critical gaps for agent decision-making.

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% ('Package names array' and 'Bypass cache'), establishing baseline 3. The description adds no additional parameter context (e.g., expected package name format, when to use ignoreCache), but doesn't need to compensate given complete schema documentation.

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 noun phrase that fails to specify what action the tool performs (check? fetch? list?). While it clarifies 'Types' refers to TypeScript, it doesn't distinguish from siblings like npmSearch or npmPackageReadme, and lacks a specific verb indicating the 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?

No guidance provided on when to use this tool versus alternatives like npmSearch, npmPackageReadme, or npmDeps. Given the crowded namespace of npm* sibling tools, the absence of selection criteria forces the agent to guess based on the cryptic 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?

Zero annotations are provided, placing full burden on the description, which discloses nothing about read-only safety, rate limits, cache behavior beyond the parameter name, error handling for invalid packages, or the structure/format of returned version 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?

While brief (3 words), this represents under-specification rather than appropriate conciseness. For a tool with no output schema and numerous siblings, the description is insufficiently sized to convey necessary 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 fails to compensate by explaining return values, pagination behavior, or version list format. Given the complexity of the npm ecosystem and 25+ sibling tools, the description is materially incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% description coverage ('Package names array', 'Bypass cache'), so the baseline is 3. The description adds no additional semantic context about parameter usage, formats, or constraints 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 'Available versions list' is tautological—restating the tool name (npmVersions) as a noun phrase without a clear verb indicating what action is performed (e.g., 'Retrieves', 'Lists'). It fails to specify the resource (npm packages) or distinguish from siblings like npmLatest 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 guidance provided on when to use this tool versus alternatives such as npmLatest (for single version) or npmSearch (for discovery). No prerequisites, filtering capabilities, or usage patterns 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?

With no annotations provided, the description carries the full burden of disclosing behavioral traits, yet it reveals nothing about whether this is read-only, what data sources it queries (npm audit? CVE databases?), rate limits, or what format the analysis returns.

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 brief at only two words, this is under-specification rather than effective conciseness. The description fails to front-load any actionable information about the tool's specific function or 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?

Despite having a complete input schema, the tool lacks an output schema and annotations. For a vulnerability analysis tool, the description inadequately describes what vulnerability data is returned (severity scores? CVE IDs? remediation advice?).

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 ('Package names array', 'Bypass cache'), establishing a baseline of 3. The description adds no additional semantic context about the expected package name format or when to bypass cache.

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 tautological given the tool name 'npmVulnerabilities' and extremely vague. It fails to specify what action is performed (scanning, reporting, auditing) or distinguish this tool from the sibling 'check_security' tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidance is provided. There is no indication of when to use this tool versus siblings like 'check_security' or other npm analysis tools, nor any prerequisites or caching behavior explained beyond the parameter 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?

With no annotations, the description must carry the full burden. It successfully identifies the sandboxed environment (Pyodide) and dependency mechanism (PEP 723). However, it omits critical behavioral details: output format, error handling behavior, filesystem/network restrictions within the sandbox, and state persistence between calls.

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?

Single sentence of 9 words with no redundancy. Main action ('Run Python') is front-loaded, and the environment qualifier ('Pyodide sandbox') appears immediately after. 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?

Given this is a 4-parameter arbitrary code execution tool with no output schema and no annotations, the description is inadequate. It lacks return value documentation, error contract details, security disclaimers, and execution limits beyond the PEP 723 mention. Complex mutation tools require richer behavioral disclosure.

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 only 25% (code described, context/timeout/requirements not). The description partially compensates by referencing 'PEP 723 requirements', which explains the requirements parameter's purpose. However, it fails to explain the 'context' parameter (variables? globals?) or 'timeout' units (milliseconds vs seconds), leaving significant semantic gaps.

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?

Clearly states the action ('Run Python') and specifies the execution environment ('Pyodide sandbox'), distinguishing it from generic code execution tools. Mentions 'PEP 723 requirements' indicating support for dependency management. Could better differentiate from sibling tools like 'execute_code' or 'execute_code_with_variables'.

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?

Lacks explicit guidance on when to use this tool versus siblings like 'execute_code' or 'execute_code_with_variables'. While 'PEP 723 requirements' hints at use cases requiring external packages, there is no 'when-not-to-use' or explicit alternative recommendations.

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, successfully disclosing rate limiting (3-call maximum) and prerequisite chaining behavior. However, it lacks disclosure of authentication requirements, error handling behavior, or the specific structure of returned documentation objects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tightly structured paragraphs with zero waste: purpose statement, prerequisite logic with exception clause, and operational limits. The 'IMPORTANT' flag appropriately emphasizes the hard rate limit. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the 100% schema coverage and explicit behavioral constraints (rate limits, prerequisites), the description is nearly complete. However, with no output schema provided and no annotations to indicate read-only status, the description could have benefited from a brief note on the return format (e.g., 'returns markdown documentation').

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?

While the schema has 100% coverage (baseline 3), the description adds significant value beyond the schema: concrete good/bad examples for the 'query' parameter ('How to set up authentication...' vs 'auth') and a critical security warning prohibiting sensitive data in queries. It also reinforces the 'libraryId' format with valid 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 opens with specific verbs ('Retrieves and queries'), identifies the resource ('documentation and code examples'), specifies the source system ('Context7'), and distinguishes itself from sibling tools like 'microsoft_docs_search' or 'npmPackageReadme' by explicitly naming the Context7 integration.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states the prerequisite ('You must call resolve-library-id first'), provides the exact exception condition ('UNLESS the user explicitly provides...'), names the alternative tool by name, and establishes hard operational constraints ('do not call this tool more than 3 times') with a clear fallback strategy.

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 burden. It discloses the selection algorithm (5 ranking factors including name similarity, documentation coverage, benchmark scores), rate limiting (3 calls max), and response handling. Does not explicitly state read-only/safe nature, though implied by 'resolves'.

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?

Lengthy but appropriately so given lack of output schema and annotations. Well-structured with clear sections (Selection Process, Response Format). Front-loaded with purpose. The Response Format section (instructing how to present results) is slightly unusual but compensates for missing output schema.

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?

Comprehensive for a 2-parameter tool with no annotations or output schema. Covers purpose, prerequisites, selection logic, presentation guidelines, and error handling ('If no good matches exist...'). Fully explains the ecosystem relationship with query-docs.

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 query and libraryName have descriptions), establishing baseline 3. Description adds value by explaining the query parameter is 'used to rank library results by relevance' and includes a security warning: 'Do not include any sensitive or confidential information... in your query.'

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 explicitly states the tool 'Resolves a package/product name to a Context7-compatible library ID' - a specific verb and resource. It clearly distinguishes from sibling 'query-docs' by stating 'You MUST call this function before query-docs', establishing the prerequisite relationship.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use ('MUST call... before query-docs') and when-not-to-use ('UNLESS the user explicitly provides a library ID'). Names the sibling alternative explicitly. Includes critical usage constraint: 'Do not call this tool more than 3 times per question.'

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

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

With no annotations provided, the description carries the full burden. It successfully discloses that this performs static analysis ('without executing it') and specifies the validation scope (security and syntax). It lacks details on return format, idempotency, or side effects, but covers the essential behavioral constraint.

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?

Single sentence with zero waste: 'Validate code' (action+target), 'for security and syntax issues' (scope), 'without executing it' (key constraint). Every word earns its place and critical information is 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?

For a simple 2-parameter tool without output schema, the description adequately covers purpose and behavioral constraints. It could be improved by describing the return value format (list of errors? boolean?) since no output schema exists, but the core functionality is sufficiently described.

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 has 100% description coverage ('Code to validate' and 'Programming language'), establishing a baseline of 3. The description adds no additional parameter-specific semantics, constraints, or examples 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?

Description provides specific verb 'Validate', target resource 'code', and scope 'security and syntax issues'. The phrase 'without executing it' clearly distinguishes this tool from execution siblings like execute_code, python_execute, and execute_code_with_variables.

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 'without executing it' provides implicit guidance for when to use this tool (when static analysis is needed). However, it fails to differentiate from similar analysis siblings like check_security, analyze_code, and check_deceptive_patterns, leaving the agent uncertain which validation/analysis tool to choose.

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