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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds value by enumerating the guide's contents, letting an agent know what to expect. It does not contradict annotations and adds contextual detail beyond the structured fields.

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 sentences, with the primary action and onboarding context front-loaded. Every word earns its place; it is concise without sacrificing informative detail.

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?

With zero required parameters, no output schema, and an onboarding guide as the deliverable, the description fully covers what an agent needs to know: when to call (start of session), what the guide contains, and that optional parameters refine it. Nothing essential 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%; each parameter (app_id, sections, task_type) has a meaningful description in the schema. The tool description itself does not add semantics beyond what the schema already provides, so it meets the baseline of 3 for high-coverage cases.

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 returns a machine-readable Fine Structure / FSe2 guide for AI agents, listing the specific topics covered (app files, entities, safe edit workflows, validation, publishing, A/B testing, secrets, platform rules). It uses a specific verb (return) and resource (guide), and the 'at the start of an MCP session' context differentiates it from siblings like get_recommended_workflow.

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 to call this at the start of an MCP session, giving clear when-to-use guidance. It does not mention when not to use it or name alternative tools, so it misses the exclusion aspect that would earn a 5.

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