validate_index

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

Even though readOnlyHint=true is already supplied, the description adds substantial behavioral transparency by detailing what operations are performed (PRAGMA integrity_check, cross-checking row count and column list against index.json, verifying index.json content hash), what stale-lock info it reports, the expected overall_status return values, and its explicit non-coverage of data correctness. This is far beyond what annotations alone reveal.

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 compact and front-loaded with the core purpose, then enumerates the exact integrity checks, then mentions the stale-lock signal and return values, and ends by constraining what the tool does not do. Each sentence contributes distinct information without filler or 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?

With a single simple parameter, readOnlyHint=true, and no output schema, this description carries all needed operational context. It explains what the tool checks, what special state it detects, what values `overall_status` can be, and the boundary against data correctness. Nothing important is missing for an agent to call it correctly.

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%, with the single `dataset` parameter already described as "Dataset identifier." The description does not add new or deeper meaning to that parameter, so the baseline score of 3 applies. It correctly focuses on the operation rather than restating the parameter.

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 opens with a specific verb and resource: "Verify an indexed dataset's on-disk integrity." It then names concrete checks (SQLite PRAGMA integrity_check, row count and column list against index.json, index.json content hash), making its function unmistakable and clearly distinct from sibling tools like summarize_dataset or get_dataset_health.

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 clearly scopes when to use the tool: it validates physical index integrity rather than underlying data correctness, and it explicitly surfaces stale-lock state from interrupted index_local runs. It does not list sibling alternatives, but the context is clear enough for an agent to know this is the integrity-validation tool rather than a general health or data-quality tool.

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