format_chart_series

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

Annotations contain only a title, so the description carries the entire burden. It clearly signals a mutating action with 'restyle', and adds behavioral details such as label_position accepted values, chart-type compatibility, and the stacked-series rejection of outside_end. It doesn't cover persistence or whether prior formatting is replaced, but the core side effect of restyling an existing chart is evident.

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 well structured with a front-loaded purpose statement, concrete use cases, and line-separated parameter notes. Every sentence adds operational value; there is no fluff or repetition of schema 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 10-parameter tool with no schema descriptions, the description covers the most complex parameters and gives enough orientation for safe invocation. The gaps minor: color format and exact data_label semantics are not explicitly stated, and there is no mention of whether changes require saving. The presence of an output schema means return values do not need to be explained, so this is reasonably complete but not exhaustive.

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?

With schema description coverage at 0%, the description must explain parameters itself. It substantially does so for series_index (0-based), label_position (allowed values and chart compatibility), number_format (Excel format string with examples), trendline (valid types), and trendline_period (window/order meaning). It leaves color, data_labels, presentation_id, slide_index, and shape_index somewhat to inference, but these are less ambiguous or self-evident from parameter names.

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: 'Restyle one series of an existing chart.' It clearly distinguishes this from siblings like add_chart, update_chart_data, and add_combo_chart by framing it as a formatting/restyling operation, and it lists concrete purposes such as pinning to a brand color, labeling a series, and adding a trendline.

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 explicit use cases: 'Use it to pin a series to a brand colour, to label just the series that carries the point rather than all of them, or to add a trendline.' This is clear context for when to invoke the tool, though it doesn't explicitly mention alternatives such as update_chart_data or save_presentation, so it stops short of the strongest possible routing guidance.

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