case-studies

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

No annotations are provided, so the description carries the behavioral transparency burden. It discloses that the tool returns a list and specifies the fields (id, parentId, title), clearly indicating a read-only enumeration. It does not mention authorization, pagination, or failure behavior, but these are less critical for a zero-parameter lookup.

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. The main action and purpose are front-loaded, and the downstream usage instruction is placed second without redundancy.

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 zero-parameter, no-output-schema tool, the description is complete: it states what is returned, names the fields, and explains how to consume the values. Nothing an agent needs to invoke it correctly or integrate it with the sibling tool is missing.

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 schema coverage is effectively complete, so the baseline is 4. The description adds no parameter-level information because none is needed; it instead explains how the results should be used downstream.

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?

States a specific verb ('Get') and resource ('all available tags'), and clearly links the purpose to filtering case studies. It distinguishes itself from the sibling search_cases by framing tags as filter inputs rather than search results.

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 tells the agent how to use the output ('Use the tag ids in the SearchCases tagIds parameter'), which clarifies its role relative to the sibling tool. It does not state exclusions or when not to use it, but the zero-parameter scope and clear purpose make the usage context unmistakable.

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 pagination behavior and the browse-all mode, but does not describe the return format, error handling, or any side effects (e.g., whether it's read-only). For a search tool, read-only is implied, but the lack of any statement about response shape or potential limits is a gap. The description adds some value beyond the schema but not comprehensive 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?

Two sentences with zero waste. The primary purpose is front-loaded, and the alternative usage (browse all) and sibling reference are woven in concisely. Every clause earns 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 tool's simplicity (4 params, 1 required, no output schema), the description covers the key usage patterns and directs the agent to the sibling for tag discovery. It does not describe the return structure, but for a search tool the response is likely a list of case studies, which is reasonably inferable. The main missing element is a statement about what fields or format to expect in the response, but overall it is adequate.

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 100%, so the baseline is 3. The description adds meaningful context by explaining the empty-query browsing pattern and pointing to GetCaseTags for tag IDs. This goes slightly beyond the schema's own parameter notes, which already mention skipping filters, but the description frames it as a user intent (browse all) and provides a discovery workflow. That extra guidance justifies a 4.

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?

States the specific verb 'Search', the resource 'DataArt case studies', and the filtering dimensions (text and/or tag IDs). It also explicitly mentions pagination, making the scope clear. It differentiates from the sibling tool by referencing GetCaseTags for tag discovery, so an agent can distinguish it immediately.

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?

Provides explicit guidance: 'Pass an empty query to browse all cases' gives a clear pattern, and 'Use GetCaseTags to discover available tag IDs before filtering' tells the agent exactly when to use the sibling tool. This is strong usage direction that leaves nothing to inference.

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