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 it states what the tool does (validation), it doesn't describe key behavioral traits such as whether this is a read-only analysis, what permissions might be required, how results are returned, or any rate limits. For a security analysis tool with zero annotation coverage, 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 concise and front-loaded, consisting of two efficient sentences that directly state the tool's purpose and scope. There's no wasted text, though it could be slightly more structured (e.g., by bullet-pointing the security checks).

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

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

Given the complexity of security validation and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a report, vulnerabilities list), how errors are handled, or any behavioral context. For a tool with no structured output and zero annotations, more detail is needed to guide the agent effectively.

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

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

Schema description coverage is 100%, so the schema already documents the single parameter ('code') with its description. The description adds no additional meaning beyond what the schema provides, such as format requirements or examples. With high schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose with a specific verb ('perform security-focused validation') and resource ('code'), and lists the types of security issues checked (XSS vulnerabilities, SQL injection risks, insecure functions). However, it doesn't explicitly distinguish this tool from sibling tools like 'validate_code' or 'explain_rule', which might have overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, when this tool is appropriate compared to sibling tools like 'validate_code' or 'list_rules', or any exclusions for its use. The agent must infer usage from the purpose 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 discloses the behavioral output (detailed explanation with examples and suggestions), which is helpful, but does not cover other traits like error handling, performance, or authentication needs. The description is accurate but lacks comprehensive behavioral context beyond the core function.

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, efficient sentence that front-loads the purpose and key details without unnecessary words. Every part ('detailed explanation', 'reasoning, bad/good examples, and fix suggestions') adds value, making it appropriately sized and structured for quick understanding.

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 moderate complexity (single parameter, no output schema, no annotations), the description is mostly complete. It clearly states what the tool does and the content of the explanation, but could improve by mentioning output format or error cases. However, it provides sufficient context for an agent to use the tool effectively in most scenarios.

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 the parameter 'ruleName' well-documented in the schema. The description does not add any parameter-specific details beyond what the schema provides, such as format constraints or examples not already covered. Baseline 3 is appropriate as the schema handles the parameter documentation adequately.

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 action ('Get detailed explanation') and resource ('a Magento coding standard rule'), with explicit content details ('reasoning, bad/good examples, and fix suggestions'). It distinguishes from siblings like 'list_rules' (which likely lists names) and 'get_rules_summary' (which might provide brief overviews).

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

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

The description implies usage when a detailed explanation of a rule is needed, but does not explicitly state when to use this tool versus alternatives like 'get_rules_summary' or 'list_rules'. No exclusions or prerequisites are mentioned, leaving usage context partially inferred rather than clearly defined.

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 mentions the tool returns patterns, code examples, and what to avoid, which gives some behavioral insight. However, it lacks details on permissions, rate limits, error handling, or response format, which are important for a tool with no annotations and no output schema.

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

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

The description is concise and front-loaded, with two sentences that efficiently convey purpose and usage. Every sentence adds value: the first states what the tool does, and the second provides context for when to use it, with no wasted words.

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

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

Given the tool's moderate complexity (1 parameter, no annotations, no output schema), the description is adequate but has gaps. It covers purpose and usage well, but lacks behavioral details like response format or error handling, which are needed for completeness without annotations or output 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 description coverage is 100%, with the parameter 'task' well-documented in the schema. The description adds minimal value beyond the schema by implying the task is development-related (e.g., 'escape HTML'), but doesn't provide additional syntax, examples, or constraints. Baseline 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: to get the correct Magento 2 way to accomplish a task, including patterns, code examples, and anti-patterns. It specifies the resource (Magento 2 patterns) and verb (get), but doesn't explicitly differentiate from sibling tools like 'explain_rule' or 'validate_code' which might overlap in domain.

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

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

The description provides clear context for when to use this tool: for 'vibe coding' - writing Magento-compliant code naturally. This implies it's for development tasks requiring best practices. However, it doesn't explicitly state when not to use it or name alternatives among siblings, such as when to choose 'validate_code' instead.

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 but only states what the tool returns without behavioral details. It doesn't disclose if this is a read-only operation, requires authentication, has rate limits, or how data is sourced (e.g., from a database or real-time analysis). This leaves significant gaps for safe invocation.

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, efficient sentence that front-loads the core action and resource, with no wasted words. It clearly communicates the tool's function without unnecessary elaboration, making it easy for an agent to parse quickly.

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

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

Given no annotations and no output schema, the description is incomplete for a tool that returns data. It doesn't specify the format of the summary (e.g., JSON structure, categories used), error handling, or what 'counts of errors and warnings' entails (e.g., per rule or total). This leaves the agent unprepared for 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?

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, focusing on the tool's purpose instead, which aligns with the baseline for zero-parameter tools.

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

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

The description clearly states the verb 'Get' and the resource 'summary of all Magento coding standard rules', specifying it's grouped by category with error/warning counts. It distinguishes from siblings like 'list_rules' by focusing on summarized statistics rather than raw listing, though the distinction could be more explicit.

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

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

No explicit guidance on when to use this tool versus alternatives like 'list_rules' or 'explain_rule' is provided. The description implies usage for aggregated rule statistics, but lacks context on prerequisites, timing, or exclusions, leaving the agent to infer based on tool names 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 full burden. It mentions filtering but doesn't disclose behavioral traits like whether it returns all rules by default, pagination behavior, rate limits, authentication requirements, or what the output format looks like (e.g., list of rule objects). For a list tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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, efficient sentence that front-loads the core purpose ('List all Magento coding standard rules') and succinctly adds filtering details. Every word earns its place with no redundancy or unnecessary elaboration.

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 complexity (a list operation with filtering), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the output contains (e.g., rule names, IDs, descriptions), how results are structured, or any limitations (e.g., max results). This makes it inadequate for an agent to fully understand how to use the tool effectively.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters (category, minSeverity, searchTerm) with clear descriptions. The description adds minimal value by restating the filtering options without providing additional syntax, examples, or constraints beyond what's in the schema, meeting the baseline for high coverage.

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

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

The description clearly states the verb 'List' and resource 'Magento coding standard rules', specifying it can filter by category, severity, or search term. This distinguishes it from siblings like 'check_security' (which likely checks code against rules), 'explain_rule' (which explains specific rules), and 'get_rules_summary' (which might provide aggregated statistics).

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 context by mentioning filtering capabilities (category, severity, search), suggesting it's for browsing or finding rules. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_rules_summary' or 'explain_rule', nor does it mention prerequisites or exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions actions (list, set, clear, info) but doesn't explain what 'set' or 'clear' do operationally (e.g., whether they modify configuration files, require permissions, or have side effects). For a tool with mutation capabilities, this is a significant gap in transparency about its behavior and potential impacts.

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 appropriately sized with three sentences: it states the purpose, lists built-in presets, and notes custom themes. Each sentence adds useful information without redundancy, and it's front-loaded with the core function. A minor improvement could be structuring the preset list more clearly, but overall it's efficient.

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

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and parameter context well but lacks details on behavioral outcomes, error handling, or return values. Without annotations or output schema, more guidance on what happens after actions like 'set' or 'clear' would enhance completeness for safe agent use.

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

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

The input schema has 100% description coverage, clearly documenting both parameters (action with enum values and themeId). The description adds value by providing examples of theme IDs (hyva, luma, breeze, porto) and mentioning custom themes as JSON files, which helps contextualize the themeId parameter beyond the schema. However, it doesn't elaborate on parameter interactions or constraints, so baseline 3 is appropriate.

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

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

The description clearly states the tool manages theme-specific coding standards for Magento, explaining that themes layer additional rules on top of base standards. It provides specific examples of built-in presets (hyva, luma, breeze, porto) and mentions custom themes, distinguishing it from siblings like list_rules or validate_code which focus on rules rather than theme management. However, it doesn't explicitly contrast with all siblings like check_security or explain_rule.

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 by listing built-in presets and custom theme options, suggesting when to use this tool for theme-related tasks. However, it lacks explicit guidance on when to choose this over alternatives like get_magento_pattern or list_rules, and doesn't specify prerequisites or exclusions for actions like 'set' or 'clear'.

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 that the tool returns violations with severity, line numbers, and fix suggestions, which is useful behavioral context. However, it doesn't mention error handling, performance characteristics, or any limitations like input size constraints.

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

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

The description is a single, well-structured sentence that front-loads the purpose and efficiently details the return format. Every word earns its place with no redundancy or unnecessary elaboration.

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 validation tool with no annotations and no output schema, the description provides good context by specifying the return format (violations with severity, line numbers, fix suggestions). However, it could be more complete by mentioning error cases or linking to the coding standards referenced.

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

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

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as explaining how 'code' should be formatted or when to choose specific 'fileType' values.

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 action ('validate code against Magento 2 coding standards') and resource ('code'), distinguishing it from siblings like 'check_security' or 'explain_rule' by focusing on standards validation rather than security checks or rule explanations.

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

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

The description implies usage when code needs validation against Magento 2 standards, but provides no explicit guidance on when to use this tool versus alternatives like 'list_rules' or 'get_magento_pattern'. It lacks clear exclusions or prerequisites.

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