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

Adds genuinely useful context beyond the annotations: it consumes inference credit (a cost signal), may return `needs_confirmation`, is persisted on the study, and surfaces above the charts in the printable report. It stops short of warning what happens to a previously existing narrative, which matters given destructiveHint=true.

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?

Two dense sentences that front-load the action and its inputs, then add operational facts. No filler, though the em-dash list of artifacts is on the edge of being a run-on.

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?

No output schema exists, so the description has to carry more weight. It does explain where the result is stored and shown and flags the `needs_confirmation` return, but with a destructive write and a 33%-covered schema, the absence of any overwrite/approval detail leaves real gaps.

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 coverage is only 33%: studyId and approvalId are undocumented in the schema, and the description never mentions any parameter by name. The implicit sourcing 'from the study's computed record' hints at studyId, but workspace override and approvalId (plausibly tied to `needs_confirmation`) are left unexplained.

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?

Specific verb (writes the report's narrative layer) and resource (the study's report), with an enumeration of the outputs produced: executive summary, key findings with numbers, recommendations. It is clearly distinguishable from the many prism_studies_draft* siblings, though it never names an alternative to route against.

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?

No when-to-use or when-not-to-use guidance, and no reference to the closely related siblings (prism_studies_draft, prism_studies_analyze, prism_studies_results) that an agent could confuse this with. The agent must infer the intended moment (post-analysis, on an existing study) entirely on its own.

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