Strasmore market data

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

The annotations already mark the operation as read-only, and the description adds useful behavioral context by explaining that the tool returns per-column type information plus non-obvious column notes and known data caveats. It does not discuss auth, rate limits, or side effects, but the absence of side effects is already conveyed by the readOnlyHint.

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 efficiently cover what the tool returns and when to call itainer. There is no redundant restatement of the tool name or title, and every clause adds useful information.

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, single-parameter introspection tool, the description is complete: it states the resource, the output, the caveats, and the correct point in the workflow. No critical missing context would prevent an agent from using 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%: the only parameter, 'table', is fully documented with a name, type, and example value. The description does not add any extra parameter-level guidance, so the baseline score of 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 the resource ('one table'), the kind of information returned (columns with ClickHouse types, notes, data caveats), and distinguishes it from siblings like list_tables by narrowing scope to a single table. It also frames the tool as a pre-SQL inspection step rather than a query execution tool like run_sql.

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 trigger: 'Call before writing SQL against a table.' This tells the agent when to use it, though it does not explicitly name alternatives or say when not to use it. The intended placement in the workflow is still clear enough to guide selection.

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 is already provided by annotations, and the description adds useful context by mentioning 'no-key access' (auth behavior) and outlining what the operation covers. It does not contradict the annotations and discloses enough for a simple no-parameter read operation.

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 compact sentence that front-loads the key idea and packs the relevant dimensions into a parenthetical. It is slightly awkward grammatically, but every element earns its place and there is no filler.

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?

There is no output schema, so the description carries the burden of explaining return values. It lists the main content categories (included access, plan additions, pricing, links) at a sufficient level for an agent to call a parameterless tool correctly, though exact output formatting is not specified.

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, so there is nothing for the description to explain beyond what the empty schema already conveys. The description adds no parameter-specific ambiguity, matching the baseline for a no-parameter tool.

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 identifies a clear resource ('no-key access', 'free account', 'paid plans') and the specific content areas (history depth, datasets, row limits, price). It is obviously distinct from the sibling tools, which all deal with tables or SQL queries, though it lacks an explicit verb like 'returns' or 'lists'.

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 through the content: an agent would use this when it needs plan or limit information. However, the description does not explicitly state when to choose this tool over alternatives, nor does it mention any exclusions or prerequisites.

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?

Annotations already declare readOnlyHint=true, and the description reinforces this by mentioning 'no-key access can read it,' implying some tables may not be readable. It also discloses the structure of each returned entry (description, filter column, readability), which goes beyond the bare read-only 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?

The description is a single, well-structured sentence that front-loads the main action, lists the market-data categories parenthetically, and ends with the crucial 'Call this first' guidance. No wasted words.

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 tool with no output schema, the description fully specifies what an agent will receive: table names with a description, a filter column, and readability status. The 'Call this first' instruction provides contextual placement, making the description sufficient for correct 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?

The tool has zero parameters, so the schema provides no information to supplement. With a parameter count of 0, the baseline is 4, and the description appropriately focuses on what the tool returns rather than parameter details.

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 ('List every table') and enumerates the exact contents returned: a one-line description, the history-window filter column, and readability under no-key access. This clearly distinguishes it from the sibling describe_table (which presumably details a single table) without needing to name it.

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 explicitly says 'Call this first,' establishing it as the initial discovery step before using siblings like describe_table or run_sql. However, it doesn't explicitly state when not to use it or name alternatives, leaving some inference to the 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?

Beyond the readOnlyHint annotation, the description discloses meaningful behavioral constraints: 500-row and 20-second limits, data history starting 2025-01-01, excluded tick-level tables, and that each result indicates which limit was hit. It also clarifies authentication requirements with 'No key needed,' which annotations do not include.

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 front-loaded sentences with no filler. The main action is stated first, followed by compact, high-value constraints and result behavior.

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 single-parameter read-only tool with no output schema, the description is complete: it explains what is run, what is returned, access requirements, limits, and result behavior. Nothing needed for a correct invocation is missing.

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 sql parameter is already documented as 'A single SELECT statement.' The description adds the read-only and limits context for the query but does not add new semantic detail about the parameter format 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 uses a specific verb and resource: 'Run one read-only ClickHouse SELECT against the global_markets database and get the rows back.' It clearly distinguishes the tool from siblings like list_tables and describe_table by framing it as actual SQL query execution rather than metadata inspection.

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 clear operational context: read-only SELECTs, no key needed, and explicit access limits. It does not name alternatives or state when not to use this tool versus list_tables/describe_table, so it misses explicit exclusion guidance but still conveys sufficient context for basic selection.

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