AgentGrade

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 a database requirement, which is useful context, but fails to describe key traits like whether this is a read-only operation, potential rate limits, error conditions, or what the output looks like (e.g., list format, timestamps). This leaves significant gaps for an agent to understand the tool's 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 two short sentences with zero waste, front-loading the core purpose and a key prerequisite. It's appropriately sized for a simple tool, though it could be slightly more structured (e.g., bullet points) for 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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format, error handling, and behavioral traits, which are crucial for an agent to use it correctly. The database requirement is helpful but insufficient for full contextual understanding.

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 clear documentation for both parameters (url as optional filter, limit with defaults). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without compensating value.

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 resource 'scan history for a URL', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'scan_url' or 'scan_compact', which might also involve scanning operations, so it misses full sibling distinction.

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 some usage context by stating 'Requires database to be configured', which implies a prerequisite. However, it doesn't explicitly guide when to use this tool versus alternatives like 'scan_url' or 'validate_x402_json', leaving usage decisions 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool is 'optimized for agent decision-making' which hints at performance characteristics, but fails to disclose critical behavioral traits like whether it's read-only/destructive, authentication requirements, rate limits, error handling, or what 'rails' and 'capabilities' specifically refer to.

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

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

The description is extremely concise with two sentences that efficiently communicate the tool's purpose and optimization. Every word earns its place with no redundant information, making it front-loaded and easy 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 the tool's scanning function with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'rails' and 'capabilities' mean in this context, doesn't describe the format or range of the 'numeric score', and provides minimal behavioral context for a tool that presumably interacts with external systems.

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 single parameter 'url' well-documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, maintaining the baseline score of 3 for adequate but not enhanced parameter 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 performs a 'compact scan' that returns specific data types (rails, capabilities, numeric score) and is optimized for agent decision-making. It distinguishes from generic scanning by specifying the limited output format, though it doesn't explicitly differentiate from sibling tools like 'scan_url'.

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 ('optimized for agent decision-making') suggesting this tool is for quick assessments rather than comprehensive scanning. However, it provides no explicit guidance on when to use this versus alternatives like 'scan_url' or 'validate_x402_json', leaving the agent to infer based on the 'compact' nature.

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 mentions the scan returns 'full results including x402, MPP, L402, discovery, bazaar, MCP, plugins, OpenAPI, and more,' which gives some output context. However, it lacks critical details like whether this is a read-only operation, potential rate limits, authentication needs, or error handling. For a tool with no annotations, this is insufficient.

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 and elaborating on results in the second. Both sentences earn their place by clarifying scope and output. It could be slightly more structured by explicitly separating purpose from output details, but it's efficient with zero 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 the tool's complexity (scanning for multiple capabilities) and lack of annotations or output schema, the description is minimally adequate. It covers the purpose and output types but misses behavioral traits and usage context. With no output schema, it should ideally describe return values more thoroughly, but the listed result types provide some 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 'url' parameter fully documented in the schema. The description adds no additional parameter semantics beyond implying the URL should be scannable for the listed capabilities. Since the schema does the heavy lifting, 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: 'Scan a URL for agent capabilities and payment protocols.' It specifies both the action (scan) and the target (URL), and mentions what it looks for (agent capabilities, payment protocols). However, it doesn't explicitly differentiate from sibling tools like scan_compact or validate_x402_json, which prevents 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 provides no guidance on when to use this tool versus alternatives. There are sibling tools like scan_compact and validate_x402_json, but no indication of when this comprehensive scan is preferred over more focused alternatives. No prerequisites, exclusions, or comparative context 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. It discloses key behavioral traits: it's a validation tool that returns errors, warnings, and suggestions, and it performs no network requests. However, it lacks details on error handling, performance characteristics, or whether it modifies input data, leaving some gaps in 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 highly concise and front-loaded, with two sentences that efficiently convey purpose, output, and a key behavioral constraint ('No network requests'). Every sentence adds essential information without redundancy, making it 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 tool's moderate complexity (validation with one parameter but no output schema), the description is adequate but incomplete. It covers purpose and key behavior but lacks details on output structure (errors, warnings, suggestions format) and doesn't reference siblings for context, leaving room for improvement in guiding the agent.

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

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

The schema description coverage is 100%, so the schema already documents the single parameter 'content' as an object for x402.json validation. The description adds minimal value beyond this, mentioning 'x402.json content' but not elaborating on format or constraints beyond what the schema implies, 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 specific action ('validate x402.json content against expected schema') and distinguishes it from siblings by mentioning 'No network requests — pure validation', which differentiates it from tools like scan_url that likely involve network operations. It uses precise verb+resource terminology.

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 validating x402.json content against a schema, with the explicit exclusion of network requests. However, it doesn't specify alternatives among siblings or when not to use it, such as compared to scan_compact which might handle different formats.

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