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

The annotations already declare readOnlyHint=true, but the description adds valuable behavioral detail: it blocks destructive SQL and leaves no trace, which goes beyond the annotation. It does not cover every possible side effect (e.g., performance or locking), but it provides meaningful context that helps an agent anticipate behavior. Since annotations carry the read-only flag, this additional context earns a 4.

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?

Three sentences with zero redundancy. The core action is front-loaded, followed by the no-trace guarantee and the destructive-SQL block, then the usage recommendation and alternative. Every sentence earns its place and the structure is logical and skimmable.

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?

The description covers the tool's purpose, its side-effect-free nature, the destructive block, and the decision between this and create_query. It does not detail return formats, but the schema already documents format and output_path. It also references data_source_id via list_data_sources in the schema, and siblings include that tool. Minor gaps (e.g., pagination or error handling) are not critical for a straightforward query executor, so a 4 is warranted.

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%—all four parameters have descriptive text in the schema. The description itself adds no parameter-specific guidance beyond what the schema already provides, such as the format behavior (csv saves to file) which is already in the schema. Baseline of 3 is appropriate when the schema fully documents parameters.

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 precise verb and resource: 'Execute a SQL query directly against a data source.' It immediately differentiates itself from the sibling create_query by noting 'no query object is created in Redash — leaves no trace.' This unambiguously identifies what the tool does and how it differs from related 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?

Explicit usage direction is provided: 'For running queries this is the DEFAULT tool. Use create_query only when user explicitly asks to save a query to Redash web UI.' This states exactly when to use this tool and when to prefer the alternative, leaving no ambiguity for an agent.

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?

The readOnlyHint annotation already establishes that this is a safe read operation, and the description is consistent with it. The description adds the scope of the result but no extra behavioral traits such as output size, pagination, or permission requirements, so it only modestly exceeds the annotation.

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?

Two short sentences, with the tool's purpose front-loaded and the prerequisite as the second sentence. No filler or redundant jargon.

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?

The tool is simple (one required parameter) and annotated as read-only, and the description explains both what is returned and how to obtain the required ID. It would only be more complete by flagging when a narrower sibling like get_table_info is more appropriate, but nothing essential is missing for a correct call.

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 coverage is 100%: the input schema already documents that data_source_id is a number and says it comes 'from list_data_sources.' The description repeats that same guidance, adding no meaning beyond 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 starts with a specific verb and resource: 'Get the full database schema (all tables and their columns) for a data source.' The parenthetical 'all tables and their columns' makes the scope concrete and separates it from siblings like get_table_info or search_schema, which target narrower information.

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?

It gives a clear prerequisite: 'Use list_data_sources first to find the data_source_id.' This tells the agent the required sequencing. It does not explicitly state when to prefer get_table_info or search_schema, so it stops short of full when-not/alternative guidance.

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?

The readOnlyHint annotation already signals a safe read operation. The description adds value by disclosing the return content—column names and types—which is beyond the annotation. It does not mention auth, errors, or rate limits, but for a simple getter this is acceptable.

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?

Two sentences with no wasted words. The purpose is front-loaded and the usage guidance is appended efficiently. Every sentence earns its place.

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?

The description covers what the tool does, what it returns, and provides one key routing hint (search_schema). It does not mention how to obtain data_source_id or contrast with get_data_source_schema, but for a simple read-only tool with full schema coverage and annotations, the remaining gaps are minor.

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 both parameters documented (data_source_id and table_name). The description only repeats the 'specific table' idea already in the schema, adding no meaningful parameter-level semantics, so the baseline 3 applies.

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 and resource: 'Get detailed column information (names and types) for a specific table.' It also distinguishes itself from the sibling search_schema by explicitly pointing to it for unknown table names, making the tool's scope clear.

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 an explicit alternative and when-not: 'Use search_schema if you don't know the exact table name.' However, it does not explicitly state when to use this tool over get_data_source_schema or mention prerequisites like obtaining data_source_id, so the guidance is good but not exhaustive.

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?

The readOnlyHint annotation already signals that this is a safe read operation. The description adds useful context by specifying the return contents (IDs, names, types) and the 'all available' scope, but it does not disclose potential limitations such as pagination, ordering, or auth requirements. This is adequate but not rich.

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 a single, efficient sentence with no filler. The action, scope, and output fields are all communicated upfront, making it easy for an agent to parse and act on.

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 zero-parameter listing tool with annotations and no output schema, the description is complete: it states what is listed, the scope, and the return fields. The low complexity means no further behavioral or structural detail is necessary.

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 schema description coverage is 100%, so there are no parameter ambiguities. The baseline for zero-parameter tools is 4; the description does not need to add parameter-level meaning because no parameters exist.

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 uses a specific verb ('List') with a clear resource ('all available Redash data sources') and explicitly states the output fields (IDs, names, types). This clearly distinguishes the tool from siblings like get_data_source_schema or get_table_info, which focus on individual source/table details.

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 does not provide any guidance on when to use this tool versus its siblings. It does not mention that this should be used to discover data source IDs before calling execute_adhoc_query, nor does it direct users to get_data_source_schema or search_schema for more detailed exploration.

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?

The readOnlyHint annotation already covers the safety profile, and the description adds the case-insensitive matching behavior. It does not disclose details such as result limits, whether matching is substring-based or pattern-based, or whether it returns only names or full schema details, so the added behavioral context is modest.

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?

Two concise sentences with no wasted words. The core behavior is front-loaded, and the usage note follows immediately, making the description scannable and efficient.

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 read-only search tool with fully described parameters and a clear use case, the description is nearly complete. The only real omission is the absence of any indication of the return shape, but that is partly mitigated by the tool's simple, search-oriented purpose.

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 documents both parameters. The description's phrase 'by name pattern' reinforces the search parameter's meaning but does not add substantive new information beyond what the schema already states.

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 action ('Search for tables and columns by name pattern') and a clear resource, with the case-insensitive behavior making the matching semantics explicit. It also differentiates the tool from exact-schema siblings like get_data_source_schema and get_table_info by focusing on fuzzy name pattern lookup.

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?

'Useful when you don't know the exact table or column name' gives a clear, practical trigger condition for selecting this tool. However, it does not explicitly mention alternative tools like get_data_source_schema or get_table_info for cases where the exact structure is already known.

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