get_data_models

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

With no annotations, the description carries the full burden. It transparently discloses that the tool makes no API calls and reads from a local cache, and warns about the sync_project prerequisite. However, it does not describe error behavior if data is not cached or the exact return format, which would enhance transparency.

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 exactly two sentences: the first declares the purpose, the second states the prerequisite. Every word earns its place, with no redundancy or filler, making it highly concise and well-structured.

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 simple local-cache read tool, the description is reasonably complete. It clarifies the local nature, the sync prerequisite, and the data types covered. It lacks detail on return values or failure behavior when data isn't cached, but given the tool's simplicity, these are not critical 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?

Schema description coverage is 100%, so the schema already fully documents all parameters. The description restates the type filter (structs, enums, collections, supabase) but adds no new semantic details beyond what the schema provides. 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 a specific verb ('Get') and enumerates the exact resources: data structs, enums, Firestore collections, and Supabase tables. It also specifies the source as 'local cache', distinguishing it from API-based sibling tools.

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 gives explicit usage context by instructing 'Run sync_project first if not cached', which is a clear prerequisite. It implies when to use the tool (after syncing) but does not explicitly state when not to use it or name alternative tools. The phrase 'No API calls' provides context that this is for cached data access.

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