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

Annotations already establish that this is a safe, read-only, closed-world read, so the bar is lower. The description adds genuine behavioral context by describing the returned content shape (happy path, per-step median hours, deviating variants with missing/extra steps), which is valuable since there is no output schema.

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?

A single front-loaded sentence with no filler; each clause (happy path, metrics, variants) earns its place. Slightly dense but efficient.

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 no output schema, the description carries the return-value burden and does so reasonably — it names the components of the payload. Combined with read-only annotations, an agent has enough to invoke it correctly, though the 'findings candidates' hint is left unexplained.

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?

Only one parameter and schema description coverage is 100%, so the schema already documents object_type with an example. The description adds only the framing 'one object type' / 'central object of the process', which is marginal beyond the schema — baseline 3 applies.

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?

States a specific verb+resource — 'Full process detail for one object type' — and enumerates what is included (happy path, step counts, median hours, deviating variants). It is clearly the detail counterpart to the sibling list_processes, though it never names that sibling explicitly.

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?

Usage is only implied: the description scopes retrieval to a single object type and hints at downstream use ('process-level findings candidates'), but gives no explicit when-to-use/when-not guidance or contrast with list_processes or get_object.

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