code-pattern-risk-scanner

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

With no annotations, the description carries the full burden but adds minimal behavioral context. It does not disclose output format, side effects, or any operational details beyond the basic action.

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

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

The description is a single sentence with no wasted words and gets straight to the point. However, its extreme brevity is more about underspecification than efficient conciseness.

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

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

Given no output schema, no annotations, and three parameters, the description is insufficient. It fails to explain return values, expected input formats, or any invocation context, making it inadequate for a 3-parameter 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 0%, and the description only clarifies the 'severity' parameter. The 'code' and 'language' parameters remain undocumented in both schema and description, leaving significant 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?

The description clearly states a detection action on 'antipatterns', using a specific verb and resource. However, it does not distinguish this from sibling tools like 'scan_patterns', which could also detect 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 provides no guidance on when to use this tool versus alternatives. It mentions an optional severity filter but lacks any contextual cues or exclusions for sibling 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, the description carries the full burden. It discloses the output range (0-100) and severity breakdown but fails to mention that this is a read-only operation, any input expectations, error behavior, or rate limits. The agent has little insight into side effects or return format.

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

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

The description is a single, focused sentence that front-loads the core function and output range. Every word adds value, with 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?

The description is too sparse for a tool with no output schema or annotations. It lacks parameter guidance, usage context relative to siblings, and output structure details (beyond 'severity breakdown'), making it incomplete for reliable tool selection and 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?

Schema description coverage is 0%, and the description does not explain the 'code' or 'language' parameters. It doesn't clarify that 'code' likely refers to source code or that 'language' is the programming language, leaving the agent to guess the parameter meanings entirely.

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 calculates a numeric risk score from 0-100 with a severity breakdown, using a specific verb and resource. However, it doesn't explicitly differentiate from sibling tools like detect_antipatterns or security_check, though the purpose is evident.

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 the tool is used when a risk score is needed, but provides no explicit guidance on when to choose it over alternatives or any exclusions. There's no mention of use cases like code review vs. vulnerability scanning, leaving the context ambiguous.

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 only states the action without explaining what happens after the scan, whether it is read-only, what output to expect, or any limitations. This is a significant gap for a tool with no other behavioral context.

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

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

The description is a single, front-loaded sentence with no filler. It is concise and every word earns its place. It sacrifices some detail for brevity but is efficient and clear.

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?

There is no output schema and no annotations, so the description must explain the tool's return value and full context. It does not mention what the scan results look like, any constraints (though the 50k char limit is in the schema), or prerequisites. The description is incomplete for a tool expected to return pattern detection results.

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

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

The schema description coverage is 100% with descriptions for both 'code' and 'language'. The description adds no additional meaning beyond implying JS/TS in 'code', which is already present in the schema. Since the schema already documents both parameters, the 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 states the specific action 'Scan' on 'JS/TS code' for '26 security and performance patterns'. This is clear and scoped. However, it does not explicitly differentiate from sibling tools like detect_antipatterns or security_check, though the mention of 26 patterns provides some uniqueness.

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

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

There is no guidance on when to use this tool versus the alternatives (detect_antipatterns, risk_score, security_check, suggest_refactor). It does not mention any conditions, alternatives, or exclusions, so it fails to help the agent choose the right tool.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions the return status and gives no indication of side effects, required permissions, or operational behavior. For a scan tool, read-only intent is implied but never stated.

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

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

The description is a single, concise sentence with no fluff. It is front-loaded with the key action and output, but its brevity comes at the cost of omitting crucial details about parameters and usage.

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 two parameters, no annotations, and no output schema, the description is inadequate. It lacks parameter explanations, usage context, and any detail about the scan's scope or return structure beyond the status values. This leaves the agent with insufficient information to invoke the tool reliably.

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 0%, and the description does not compensate. Neither 'code' nor 'language' parameters are mentioned, leaving their purpose and constraints completely unexplained. The description adds zero semantic value for the 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 tool performs a security-focused scan and returns a categorical status (vulnerable | at-risk | secure). It defines the output distinctly, though it does not explicitly differentiate itself from sibling tools like detect_antipatterns or risk_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 offers no guidance on when to use this tool versus its siblings. It simply states what it does without any context about preferred use cases or exclusions, leaving the agent to infer suitability.

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

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

With no annotations, the description carries the full burden. It discloses that the tool produces 'suggestions' (implying non-destructive analysis) and describes the output format as prioritized and step-by-step. However, it does not mention language handling, input requirements, or any potential side effects, leaving some ambiguity.

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

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

The description is a single, front-loaded sentence with zero filler. Every word earns its place, making it highly concise and easy to parse.

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

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

Given the lack of annotations, no output schema, and 0% parameter coverage, the description is insufficient for an agent to fully understand input expectations or output details. It hints at the output format but does not specify required inputs or how the tool behaves, leaving significant gaps for a two-parameter 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 0%, so the description must compensate by explaining 'code' and 'language', but it does not mention either parameter. The parameter names are self-explanatory, but the description adds no meaning beyond the schema, which lacks any field descriptions.

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 'Get prioritized step-by-step refactoring suggestions' clearly states a specific action (get) and resource (refactoring suggestions), with qualifiers that add value. It is distinct from sibling tools (detect_antipatterns, risk_score, etc.) which focus on analysis, not refactoring guidance.

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 sibling tools, nor are any prerequisites or alternative scenarios mentioned. The description only implies that you use it for refactoring suggestions, but it does not explicitly differentiate it or provide usage context.

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