RoloCache

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

No annotations provided, so description carries full burden. It describes the returned metadata and implies a read-only, informational operation. Could mention if the data is cached or any side effects, but overall transparent.

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?

Two sentences with no wasted words. Front-loaded with purpose, then provides specific examples and usage guidance. Excellent structure.

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?

With no parameters and an output schema present, the description is complete. It tells the agent exactly what to expect and when to use it. No gaps.

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, so schema coverage is 100%. The description adds value by explaining what the output contains, which is beyond the schema. Baseline 4 for 0 params, but the extra context earns a 5.

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 returns live metadata about the RoloCache catalog, listing specific items (vendors count, protocol names, has_agent_interface values, tags). It distinguishes from siblings by advising to call this first when unsure of filter values or to get coverage.

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?

Explicitly tells the agent to call this tool first when unsure of valid filter values or to understand catalog coverage before searching. While it doesn't specify when not to use it, the guidance is clear and sufficient for most cases.

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?

Despite no annotations, description discloses response structure (data, outpost_dispatch, context_advisory), protocol status meanings, and advisory URL fetching requirement. Provides comprehensive behavioral expectations without contradiction.

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?

Description is front-loaded with purpose and parameter explanation, then structured into response fields and workflow. Slightly verbose but each sentence adds value; could be marginally tighter.

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 output schema exists, description still fully explains all response fields (data, outpost_dispatch, context_advisory, protocols with statuses) and workflow context (close loop with report_to_outpost). Complete for a single-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?

With schema coverage at 0%, description fully compensates by explaining vendor_id as slug form, giving examples ('booking-com', 'delta', 'navan'), and instructing to get valid IDs from lookup_vendors. Adds significant value beyond raw schema.

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?

First sentence clearly states action and resource: 'Fetch the full AgentRouting record for a specific vendor, wrapped in a feedback request envelope.' Distinguishes from siblings by referencing lookup_vendors for ID retrieval and report_to_outpost for post-task closing.

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?

Explicitly tells agent to get vendor_id from lookup_vendors() first, and to close the loop with report_to_outpost after task completion. Provides clear context for when to use, though does not explicitly mention when not to use this 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, the description fully covers behavior: search semantics, protocol exact match, has_agent_interface values, result inclusion criteria, and suggested follow-up via get_vendor().

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?

Well-structured: one-sentence purpose, then parameter details with examples. No fluff, every sentence is informative.

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?

Comprehensive for a search tool: lists result fields and suggests follow-up. Could mention pagination or limits, but not necessary given the context. Output schema exists but not shown; description covers output sufficiently.

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 coverage is 0%, but description provides detailed semantics for each parameter: query examples, protocol valid values and behavior, has_agent_interface meaning of 'partial'. Greatly enriches the schema.

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?

Starts with clear verb+resource: 'Search the RoloCache catalog and return matching vendors.' Distinguishes from siblings like get_vendor which retrieves a single record.

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?

Explains all parameters are optional and combinable, including the no-parameter case returning all vendors. Does not explicitly contrast with siblings but context signals make the distinction 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?

No annotations exist, so the description fully discloses behavior. It explains that notes are untrusted, that friction fields become meaningful conditionally, and that reports improve the record. It does not mention side effects beyond that, but the tool is a benign report submission, so this is adequate.

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 moderately long but well-structured with bullet points and clear sections. Every sentence adds value: purpose, importance, parameter details, conditional logic, and alternative usage. It is front-loaded with the core action.

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 covers nearly all aspects: purpose, parameters, usage instructions, and alternative. It does not describe the output schema or the response structure post-submission, but given the tool is a one-way report, the description is sufficiently complete.

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%, but the description thoroughly explains each parameter: response_id and vendor_id come from get_vendor(), protocol_attempted is the protocol used, booleans are defined, friction details are conditional, and notes is optional and untrusted. This adds full meaning beyond field names.

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 'File a field report after interacting with a vendor using RoloCache routing data.' It clearly identifies the tool's action and resource. Sibling tools like get_vendor and lookup_vendors are query-oriented, making this distinct as a write operation.

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: it should be used after interacting with a vendor and explains that response_id and vendor_id come from get_vendor(). It also includes an alternative HTTP endpoint. However, it does not explicitly compare to siblings or state when not to use it.

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