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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Adds two numbers' implies a simple calculation but reveals nothing about error handling (e.g., overflow, invalid inputs), performance characteristics, or what the output looks like. For a tool with zero annotation coverage, this is insufficient 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 maximally concise with just three words that directly convey the core functionality. There is zero wasted language, and the information is front-loaded appropriately for such a simple 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?

Given the tool's simplicity (basic arithmetic operation with 2 parameters) and 100% schema coverage, the description is minimally complete. However, the lack of output schema means the description should ideally mention what is returned (e.g., a sum), but doesn't. The absence of annotations also leaves behavioral gaps unaddressed.

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 parameters clearly documented as 'First number' and 'Second number'. The description adds no additional parameter semantics beyond what the schema already provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even without parameter info in the description.

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 ('Adds') and resource ('two numbers'), making the purpose immediately understandable. It doesn't differentiate from siblings, but since none of the sibling tools appear to be arithmetic operations, this is adequate. The description avoids tautology by specifying what is being added.

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 any prerequisites, constraints, or suggest other tools for different mathematical operations. While the sibling list doesn't include obvious alternatives like 'subtract' or 'multiply', the lack of any usage context leaves the agent without 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states it 'demonstrates how annotations can be used', which doesn't reveal whether this is a read-only operation, if it has side effects, what it returns, or any performance characteristics. For a tool with no annotation coverage, this leaves critical behavioral traits unspecified.

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, straightforward sentence that efficiently conveys its core idea without unnecessary words. It's appropriately sized for a demonstration tool, though it could be more front-loaded with actionable information about what the tool actually produces or does.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a sample annotated message, a demonstration output), how the parameters affect the demonstration, or any educational context. For a tool with 2 parameters and no structured output documentation, more detail is needed to make it fully usable.

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 clear descriptions for both parameters ('includeImage' and 'messageType'), including an enum for messageType. The description adds no parameter-specific information beyond what the schema already provides. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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 tool 'demonstrates how annotations can be used to provide metadata about content', which gives a vague purpose but doesn't specify what the tool actually does operationally. It mentions 'annotations' and 'metadata' but lacks a clear verb+resource combination. Compared to siblings like 'echo', 'add', or 'getResourceLinks', it doesn't clearly differentiate its specific function beyond being a demonstration 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any specific contexts, prerequisites, or exclusions. Given siblings like 'echo' (for echoing input) or 'sampleLLM' (for LLM sampling), there's no indication of when this demonstration tool would be preferred over others for testing or educational purposes.

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. 'Echoes back the input' implies a read-only, non-destructive operation, but it lacks details on output format, error handling, or any constraints like rate limits. This is a significant gap for a tool with zero 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 extremely concise with just three words, front-loaded and zero waste. Every word earns its place by directly conveying the core function without unnecessary elaboration, making it highly 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 simplicity (1 parameter, no output schema), the description is incomplete. It doesn't explain the return value (e.g., what 'echoes back' means in practice) or provide context for use among siblings. Without annotations or output schema, more detail is needed to fully inform an 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 input schema has 100% description coverage, with the 'message' parameter fully documented. The description adds no additional meaning beyond what the schema provides, such as examples or usage context. According to the rules, with high schema coverage (>80%), the baseline is 3 even without param info in the description.

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 'Echoes back the input' clearly states the tool's function with a specific verb ('echoes') and resource ('input'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'printEnv' or 'sampleLLM' that might also output data, so it doesn't reach the highest 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. With siblings like 'printEnv' (prints environment variables) and 'sampleLLM' (likely generates text), there's no indication of when 'echo' is appropriate, such as for testing or simple output, leaving usage unclear.

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 states the tool returns multiple resource links but doesn't explain what a 'resource link' is, how they are selected, whether there are permissions or rate limits, or what the output format looks like. This leaves significant gaps in understanding 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 a single sentence that is efficient and front-loaded, stating the core purpose without unnecessary words. However, it could be more structured by including key details like parameter context or usage distinctions.

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 returning 'resource links' with no annotations or output schema, the description is incomplete. It fails to clarify what resource links are, how they differ from sibling tools, or what the return values entail, making it inadequate for effective 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?

The input schema has 100% description coverage, with the 'count' parameter clearly documented in the schema. The description adds no additional meaning beyond what the schema provides, as it doesn't mention parameters at all. 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 states the tool 'Returns multiple resource links that reference different types of resources', which provides a basic purpose but is vague about what 'resource links' are and what 'different types of resources' means. It doesn't clearly distinguish this tool from sibling tools like 'getResourceReference' or 'getTinyImage', leaving ambiguity about when to use each.

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 is no mention of context, prerequisites, or exclusions, and it doesn't reference sibling tools like 'getResourceReference' to help differentiate usage scenarios.

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 states the tool returns something but doesn't explain what a 'resource reference' entails (e.g., format, content, or how it's used by MCP clients), whether it's a read-only operation, or any potential side effects. This is inadequate for a tool with no annotation coverage, as it leaves key behavioral traits unspecified.

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 states the core function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly. Every part of the sentence contributes to the purpose, earning 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 complexity (a tool that returns a reference with no output schema) and lack of annotations, the description is incomplete. It doesn't explain what the returned 'resource reference' is, how it's structured, or its use cases, leaving gaps in understanding the tool's behavior and output. This is insufficient for effective 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 description adds no parameter semantics beyond what the input schema provides. The schema has 100% description coverage, clearly documenting the 'resourceId' parameter with its type, range, and requirement. Since the description doesn't elaborate on parameters, it meets the baseline of 3 for high schema coverage without adding 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 states the tool 'Returns a resource reference that can be used by MCP clients', which provides a basic purpose (verb 'returns' + object 'resource reference'). However, it's vague about what a 'resource reference' actually is and doesn't distinguish this from sibling tools like 'getResourceLinks' or 'getTinyImage' that might also return references or resources. The purpose is stated but lacks specificity.

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. The description doesn't mention any context, prerequisites, or exclusions, and it doesn't reference sibling tools. This leaves the agent with no information on appropriate usage scenarios, making it rely solely on the tool name and input schema.

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 fails completely. It doesn't indicate whether this is a read-only operation, whether it has side effects, what authentication might be required, or any rate limits. The single sentence provides no behavioral context 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 extremely concise - just three words - but this brevity comes at the cost of being under-specified rather than efficiently informative. While it's front-loaded with the core action, it lacks the necessary explanatory content that would make it genuinely helpful to an agent.

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 that there are no annotations, no output schema, and the description provides minimal information, this is incomplete for agent understanding. The tool name suggests it retrieves some kind of image resource, but the description doesn't explain what 'MCP_TINY_IMAGE' represents, what format it returns, or why one would use this versus other resource-fetching tools on the server.

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 the input schema has 100% description coverage (though empty). The description appropriately doesn't waste space discussing nonexistent parameters. With no parameters to document, the baseline score of 4 reflects that the description doesn't need to compensate for any parameter documentation 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 'Returns the MCP_TINY_IMAGE' is a tautology that essentially restates the tool name 'getTinyImage' with minimal additional information. While it does specify the verb 'Returns' and resource 'MCP_TINY_IMAGE', it doesn't explain what this resource represents or what purpose it serves, making it vague rather than specific.

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 absolutely no guidance about when to use this tool versus alternatives. There's no mention of context, prerequisites, or comparison with sibling tools like 'getResourceLinks' or 'getResourceReference' that might serve similar purposes. This leaves the agent with no usage direction.

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. It mentions 'long running operation' and 'progress updates', which hints at asynchronous behavior and status reporting, but doesn't specify timeout expectations, cancellation support, error handling, or what 'progress updates' actually entail. This leaves significant behavioral gaps for a tool explicitly about long-running operations.

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 directly states the tool's purpose. There's no wasted language or unnecessary elaboration. It's appropriately sized for what it communicates.

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 tool about long-running operations with no annotations and no output schema, the description is insufficient. It doesn't explain what the operation actually does, what progress updates look like, how results are returned, or any error conditions. The agent lacks critical context needed to properly use 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 schema already fully documents both parameters (duration and steps). The description adds no additional parameter semantics beyond what's in the schema. The baseline score of 3 is appropriate when the schema does all the parameter documentation work.

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 tool 'demonstrates a long running operation with progress updates', which provides a general purpose but lacks specificity about what resource or domain it operates on. It distinguishes from siblings by mentioning 'long running' and 'progress updates', but doesn't specify what exactly is being operated on or demonstrated.

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 any prerequisites, constraints, or comparison to sibling tools. The agent must infer usage purely from the name and description without explicit direction.

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 tool's behavior (prints all environment variables) and its purpose (debugging), but lacks details like output format, security implications (e.g., exposing sensitive data), or performance characteristics. This is adequate but has gaps.

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 ('Prints all environment variables') and adds value with the debugging context. Every word earns its place with no 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 simplicity (0 parameters, no output schema, no annotations), the description is complete enough for basic use. However, it lacks details on output format (e.g., structured vs. plain text) and potential risks (e.g., exposing secrets), which could be important for debugging 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?

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately does not discuss parameters, earning a high baseline score for not adding unnecessary information.

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 ('Prints') and resource ('all environment variables'), and distinguishes its debugging purpose from sibling tools like 'echo' or 'getResourceLinks' which serve different functions. It goes beyond a tautology by explaining what gets printed.

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 explicitly states when to use this tool ('helpful for debugging MCP server configuration'), providing clear context. However, it does not specify when not to use it or name alternatives among siblings, which prevents a perfect score.

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 'sampling' but doesn't disclose behavioral traits like whether it's read-only or mutative, potential rate limits, authentication needs, or what the output format is (e.g., text, tokens). This is inadequate 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 a single, efficient sentence with no wasted words. It's appropriately sized and front-loaded, clearly stating the core purpose without unnecessary elaboration, earning a high score for 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 the complexity of LLM sampling, no annotations, and no output schema, the description is incomplete. It lacks details on behavior, output format, and usage context, which are crucial for an agent to effectively invoke this tool. It should provide more guidance to compensate for the missing structured data.

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 fully documents the two parameters ('prompt' and 'maxTokens'). The description adds no meaning beyond this, such as explaining how sampling interacts with the prompt or token limits. Baseline 3 is appropriate as the schema handles 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 states the tool 'Samples from an LLM using MCP's sampling feature', which provides a basic verb+resource ('samples from an LLM') but lacks specificity about what sampling entails (e.g., generating text, completing prompts) and doesn't distinguish it from sibling tools like 'annotatedMessage' or 'echo' that might involve LLM interactions. It's vague but not tautological.

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 alternatives. It doesn't mention any context, prerequisites, or exclusions, such as when to prefer 'annotatedMessage' or 'echo' for similar tasks. This leaves the agent without direction for tool selection.

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 states the tool returns content but doesn't describe any behavioral traits such as rate limits, authentication requirements, error conditions, or what happens when invalid input is provided. The mention of 'output schema for client data validation' suggests some validation behavior, but this is not elaborated.

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 gets straight to the point. It's appropriately sized for a simple tool with one parameter. However, it could be slightly more front-loaded by specifying what type of structured content is returned earlier in the description.

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 an output schema (which handles return value documentation), a simple input schema with 100% coverage, and no complex annotations, the description is reasonably complete. It covers the basic purpose and hints at validation use. The main gap is lack of specificity about what structured content is actually returned.

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 the single parameter 'location' clearly documented as 'City name or zip code.' The description adds no additional meaning beyond what the schema provides - it doesn't explain how the location parameter affects the returned content or provide examples. Baseline score of 3 is appropriate since 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 states the tool 'Returns structured content' which indicates a read operation, but it's vague about what specific content is returned. It mentions 'client data validation' but doesn't specify what kind of structured content (e.g., weather data, business listings, etc.). The purpose is clear enough to understand it's a retrieval tool but lacks specificity about the resource being accessed.

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 any sibling tools or specific contexts where this tool is preferred. The phrase 'for client data validation' hints at validation use cases, but this is too general to serve as practical guidance for tool selection.

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 compresses files and returns a data URI, but lacks details on behavioral traits such as error handling (e.g., invalid URIs), performance (e.g., size limits), or side effects (e.g., network requests for URIs). This is inadequate for a tool that processes external resources.

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, input, and output without unnecessary details. It is front-loaded with the core action and avoids redundancy, making it 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 complexity (processing multiple external files) and lack of annotations or output schema, the description is insufficient. It doesn't explain return values (e.g., structure of the data URI), error conditions, or limitations, leaving gaps for safe and effective tool invocation by an AI 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?

Schema description coverage is 100%, so the schema fully documents the 'files' parameter as a mapping of file names to URLs. The description adds marginal value by specifying that URIs can be data URIs and clarifying the mapping purpose, but doesn't provide additional syntax or format details beyond what the schema already covers.

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 ('compresses'), the resource ('provided resource files'), and the output ('to a zip file, which it returns as a data URI resource link'). It distinguishes itself from sibling tools like 'getResourceLinks' or 'getTinyImage' by focusing on compression rather than retrieval or image processing.

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 prerequisites (e.g., file availability), exclusions (e.g., unsupported file types), or compare it to sibling tools like 'add' or 'structuredContent' for handling multiple files. Usage is implied but not explicitly stated.

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