mcp-dashboards

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

The description adds valuable behavioral context beyond what annotations provide: it explains the auto-inference logic for bar types ('auto-infers add/sub/total if type omitted') and specifies the inference rules ('first/last=total, positive=add, negative=sub'). Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description appropriately focuses on chart-specific behavior rather than repeating safety information.

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 perfectly concise with two sentences that each earn their place: the first establishes the chart type and purpose, the second explains the key behavioral feature (auto-inference). No wasted words, front-loaded with the essential information, and structured to immediately convey what makes this tool unique.

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 tool's complexity (7 parameters, chart rendering), rich annotations, and 100% schema coverage, the description provides good contextual completeness. It explains the chart's purpose and key behavioral feature (auto-inference). The main gap is lack of output information (no output schema), but for a visualization tool where the output is implicitly a rendered chart, this is less critical than for data-returning tools.

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 100% schema description coverage, the schema already documents all 7 parameters thoroughly. The description adds some semantic context about the 'type' parameter's auto-inference behavior, but doesn't provide additional meaning for other parameters beyond what's in their schema descriptions. This meets the baseline expectation when schema coverage is complete.

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 specific verb 'render' and resource 'waterfall chart', with the explanatory phrase 'What drove the change?' that captures the chart's analytical purpose. It distinguishes from siblings by explicitly describing the waterfall chart's unique characteristics ('cascading bars showing how individual items add up or subtract to reach a total'), differentiating it from other chart types in the sibling list.

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 implies usage context through the phrase 'What drove the change?' which suggests analyzing contributions to a total, but doesn't explicitly state when to use this versus alternatives like render_bar_chart or render_variance_chart. No explicit exclusions or alternative tool recommendations are provided, leaving the agent to infer appropriate usage scenarios from the chart type description alone.

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