search_abstractions

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

With no annotations provided, the description carries the full burden. It discloses the ranking order, which is a useful behavioral trait. However, it does not explicitly state the operation is read-only or describe any potential side effects, though that is implied for a search tool.

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, front-loaded with the core action and the ranking rule. Every sentence is informative and concise, with zero waste or repetition.

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 low-complexity search tool with an output schema available, the description covers the main purpose and ranking detail adequately. The only gap is that it does not mention usage context relative to sibling tools, but given the simplicity and schema support, it remains complete enough for 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?

Schema description coverage is 100%, so the baseline is 3. The schema already explains `query`, `fields` (summary/full), and `max_results` (1-100). The description adds no additional parameter semantics beyond what the schema provides, so a 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 clearly states 'Search the abstraction index by keyword,' identifying the specific verb and resource. It distinguishes from sibling tools like `search_code` by targeting the abstraction index, and the ranking criteria (exact name > name-contains > tag > layer/kind) further clarifies scope.

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?

Usage is implied as a keyword search for abstractions, but there is no explicit guidance on when to use this tool over alternatives like `search_code` or `read_doc`. No exclusions or alternative references are provided, so it lacks direct 'when vs. when-not' guidance.

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