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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it's a write operation ('Save'), returns a shareable URL, has a time-to-live constraint ('valid for 2 hours', 'auto-expiring data'), and mentions use cases that imply it's for temporary storage. It doesn't cover rate limits or authentication needs, but provides substantial context beyond basic function.

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 appropriately sized and front-loaded: the first sentence states the core function, followed by specific use cases and behavioral details. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI 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 the complexity (a write operation with 4 parameters), no annotations, and no output schema, the description is largely complete: it covers purpose, usage, key behaviors (ephemeral storage, URL return), and complements the well-documented schema. However, it doesn't explicitly describe the return value format beyond 'shareable URL', which could be more detailed given the lack of output schema.

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 baseline is 3. The description adds value by explaining the purpose of saving data ('Store your reasoning state, large JSON structures, or any data') and the outcome ('get a shareable URL'), which complements the schema's parameter descriptions. However, it doesn't provide additional details on parameter usage beyond what's in 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?

The description clearly states the specific action ('Save objects to ephemeral cloud storage') and resource ('objects'), distinguishing it from the sibling tool 'get_object' which presumably retrieves rather than stores. It provides concrete examples of what can be stored ('reasoning state, large JSON structures, or any data') and the outcome ('get a shareable 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 explicitly lists multiple scenarios for when to use this tool ('Perfect for: caching contexts before token limits, bridging multi-agent workflows, storing intermediate results, sharing data between sessions, or temporary data storage'), providing clear context. It also implies when not to use it by specifying the ephemeral nature ('auto-expiring data', 'valid for 2 hours'), suggesting alternatives for permanent storage.

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 that the tool is for reading/retrieving data, which implies it's non-destructive, but doesn't specify permissions, rate limits, error conditions, or what happens if the object ID is invalid. For a cloud storage tool with zero annotation coverage, this leaves significant gaps in understanding its 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 sentences with zero waste—each sentence adds essential information (what the tool does and when to use it). It's front-loaded with the core purpose and efficiently structured 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?

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and usage but lacks details on behavioral aspects like error handling or return values, which are important for a cloud storage retrieval tool. Without annotations or output schema, more context would improve 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 parameter 'object_id' documented as 'The object ID (8-character identifier from the URL)'. The description adds minimal value beyond this by mentioning 'using its ID' but doesn't provide additional context like format examples or constraints. This meets the baseline for high schema 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 tool's purpose with specific verbs ('Retrieve data', 'read data') and identifies the resource ('cloud storage', 'using its ID'). It distinguishes from the sibling 'create_object' by focusing on retrieval rather than creation, though it doesn't explicitly name the sibling. The description avoids tautology by explaining functionality beyond the tool name.

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 ('to read data that another agent (or yourself) saved previously'), which implicitly distinguishes it from the sibling 'create_object' for saving data. However, it doesn't explicitly state when not to use it or name alternatives, keeping it from a perfect score.

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