data_get_pine_tables

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool reads data and returns formatted text rows per table, which covers the core behavior. However, it does not describe edge cases like absent tables, multiple matching studies, or whether the data reflects the current chart state.

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 short sentences deliver the essential information with no filler. The primary action and target resource are front-loaded, and the parameter guidance is compact. 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 tool is simple: one optional parameter and no output schema. The description adequately covers the return format and the filtering mechanism. Combined with the fully self-documenting schema, the main missing context is minor—such as how multiple tables are represented or whether an empty result is possible—so it remains sufficiently complete 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?

Schema description coverage is 100%, so the baseline is 3. The description repeats the study_filter parameter and says it targets a specific indicator, which echoes the schema's 'Substring to match study name. Omit for all.' It adds no material new 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 opens with a specific verb and resource: 'Read table data drawn by Pine Script indicators (table.new).' It clearly distinguishes this tool from siblings like data_get_pine_lines, data_get_pine_labels, and data_get_pine_boxes by focusing on tables. The added return detail, 'formatted text rows per table,' further disambiguates its purpose.

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 context for when to use the tool: whenever table data from Pine Script indicators is needed, and it mentions using study_filter to target a specific indicator. It does not explicitly name alternatives or exclusion cases, but the 'table data' scope makes the appropriate use case evident.

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