fm_analyze_portal_data

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool analyzes portal structures and can obtain sample data, but doesn't describe what 'analyze' entails operationally (e.g., is it read-only, does it require specific permissions, what's the response format, are there rate limits?). For a tool with no annotation coverage, this leaves significant behavioral gaps, though it does mention Data API support as a minor contextual hint.

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 appropriately sized with two sentences that efficiently convey the core functionality and technical context. It's front-loaded with the main purpose, followed by a supporting detail about Data API support. There's no wasted verbiage, though the second sentence could be more tightly integrated with the first for better flow.

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 (analyzing portal structures with optional sample data), no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., read/write nature, error handling), output format, and how it differs from sibling tools. The mention of Data API support is insufficient to compensate for these gaps, making it inadequate for an agent to fully understand the tool's context and usage.

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 all three parameters (layout, includeSampleData, sampleLimit) with descriptions. The description adds marginal value by mentioning 'sample data (optional)' which aligns with includeSampleData, but doesn't provide additional semantics beyond what's in the schema. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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 tool's purpose: analyzing portal structures within a specified layout, obtaining field definitions, inferred related table names, and optional sample data. It uses specific verbs like 'analyze' and 'obtain' with clear resources (portal structures, field definitions, table names, sample data). However, it doesn't explicitly differentiate from sibling tools like fm_get_layout_metadata or fm_infer_relationships, which appear related to metadata analysis.

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 provides no guidance on when to use this tool versus alternatives. It mentions that the feature is 'fully supported by the Data API,' but this is generic technical context rather than usage guidance. There's no indication of prerequisites, typical use cases, or comparisons with sibling tools like fm_get_layout_metadata or fm_infer_relationships, leaving the agent to infer usage context.

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