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

Even with readOnlyHint=true already in annotations, the description adds meaningful behavioral context: row counts are 'cached 5 minutes', the database is a local SQLite store, and the error 'database has not been built yet' is explained as the ingest pipeline not having run. This goes well beyond the annotation and prepares the agent for real-world 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 long but tightly organized with clear sections (Args, Returns, Key objects, Examples, Use when, Errors). Every section earns its place: the schema details in 'Key objects' are essential for understanding the database, and the error note prevents confusion. It is front-loaded with the core purpose.

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 of a database schema tool, the description is remarkably complete: it explains key tables and fields, identifies the preferred views, provides example usage, and covers failure modes. The presence of an output schema further reduces the need to explain return values, but the description already does so.

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 description explicitly states 'Args: (none)', eliminating ambiguity. Per the baseline for zero-parameter tools, this is a 4. The return-value breakdown is also present, helping the agent understand how the tool's output will be structured.

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 states a specific verb ('Inspect') and resource ('schema of the local finbridge database') and enumerates exactly what is returned: tables, views, columns, row counts, example queries. It clearly distinguishes itself from siblings by explicitly disclaiming live market data and pointing to query_db, making it easy to tell apart.

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 explicit usage conditions: 'Use when: preparing a query_db, or checking ingest coverage.' It also gives a direct exclusion: 'Don't use for live market data (use the dart_/edgar_/fred_/crypto_ tools).' This is exemplary when/when-not guidance.

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