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 doesn't disclose critical traits like whether it's read-only, has rate limits, requires authentication, or how it handles errors, leaving significant gaps for a tool with no annotation coverage.

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, stating the core purpose in the first sentence. The second sentence adds context about 'vibe coding' without redundancy. It could be slightly more structured, but overall, it's efficient with minimal waste.

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 provides basic purpose and usage but lacks details on behavioral traits, error handling, or return format. It's adequate for a simple query tool with one parameter, but doesn't fully compensate for the missing structured data, leaving room for improvement in 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?

The input schema has 100% description coverage, with the 'task' parameter clearly documented. The description adds minimal value beyond the schema by implying the task should be coding-related (e.g., 'read a file'), but doesn't provide additional syntax, format details, or examples. 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, returning patterns, code examples, and anti-patterns. It specifies the resource (Magento 2 patterns) and verb (get), though it doesn't explicitly differentiate from sibling tools like 'explain_rule' or 'validate_code'.

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

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

The description provides implied usage guidance by mentioning 'vibe coding' for writing Magento-compliant code naturally, suggesting it's for coding tasks. However, it lacks explicit when-to-use vs. alternatives, such as how it differs from 'explain_rule' or 'validate_code', and doesn't specify exclusions or prerequisites.

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 describes the output format ('summary...grouped by category, showing counts of errors and warnings'), which is useful. However, it lacks details on potential side effects (e.g., is this a read-only operation?), performance considerations (e.g., latency, rate limits), or error handling. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, well-structured sentence that efficiently conveys the tool's purpose and output format. It is front-loaded with the main action ('Get a summary') and avoids unnecessary details. Every part of the sentence earns its place by specifying the resource, grouping method, and data included.

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 (simple read operation with no parameters) and the absence of annotations and output schema, the description is minimally adequate. It explains what the tool does and the format of the output, but it doesn't cover behavioral aspects like safety or performance. For a tool with no structured data beyond the input schema, the description provides a basic understanding but could be more complete by addressing missing behavioral context.

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

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

The tool has 0 parameters, and the schema description coverage is 100% (as there are no parameters to describe). The description doesn't need to add parameter semantics, so it appropriately focuses on the tool's purpose and output. A baseline of 4 is applied since no parameters exist, and the description doesn't attempt to explain non-existent 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 clearly states the tool's purpose: 'Get a summary of all Magento coding standard rules grouped by category, showing counts of errors and warnings.' It specifies the verb ('Get'), resource ('Magento coding standard rules'), and output format ('summary...grouped by category, showing counts of errors and warnings'). However, it doesn't explicitly differentiate from sibling tools like 'list_rules' or 'explain_rule', which might offer similar rule-related information.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_rules' (which might list individual rules) or 'explain_rule' (which might provide detailed explanations), nor does it specify prerequisites or contexts for usage. 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 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 that themes layer additional rules and lists built-in presets, but fails to describe key behaviors such as whether changes are persistent, if permissions are required, what happens when a theme is set/cleared, or error handling. This leaves significant gaps for a tool with mutation actions like 'set' and 'clear'.

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

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

The description is appropriately sized with three sentences that efficiently cover purpose, built-in themes, and custom themes. It's front-loaded with the core function and avoids redundancy, though it could be slightly more structured by separating usage notes from feature lists.

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 with multiple actions (list, set, clear, info) and no output schema or annotations, the description is incomplete. It doesn't explain return values, error cases, or the impact of actions like 'set' or 'clear', which is inadequate for a mutation tool without structured support.

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 minimal value by listing example theme IDs (e.g., 'hyva', 'luma') and mentioning custom themes as JSON files, but doesn't provide additional syntax, format details, or constraints beyond what the schema specifies. This meets the baseline for high schema coverage.

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

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

The description clearly states the tool manages theme-specific coding standards for Magento, explaining that themes layer additional rules on top of base standards. It distinguishes this from sibling tools like 'list_rules' or 'validate_code' by focusing on theme management rather than rule listing or validation. However, it doesn't explicitly contrast with all siblings (e.g., 'get_magento_pattern'), keeping it from a perfect score.

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 mentioning custom themes, suggesting it's for handling theme-related standards. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_rules_summary' or 'explain_rule', and doesn't specify prerequisites or exclusions, leaving usage context somewhat vague.

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.