Read the morning report

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

Annotations already cover readOnly/idempotent/non-destructive, so the bar is lower, and the description adds real context beyond them: the underlying GET endpoint, required reports:read scope, full_content data sensitivity, and the explicit statement that no model call occurs. These are operational traits the agent cannot infer from the annotation block.

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 lead sentence front-loads purpose and payload, followed by compact metadata lines that are each short and scannable. The scope/idempotency lines are somewhat boilerplate but carry concrete constraints, so nothing is egregiously wasted.

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?

An output schema exists, so return-value explanation is not required, and the description still covers auth scopes, sensitivity, workspace-override behavior, and the client-side summarization expectation. The one gap is the failure to disambiguate from the luca_morning_report sibling.

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 100%, so the baseline is 3, but the description goes further by explaining the semantics of omission: workspaceId/workspaceSlug override 'the default workspace configured by environment.' That resolves the ambiguity of what happens when both optional params are absent.

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 resource and payload: a structured 24h review-queue digest of items plus counts for the coach. It clearly distinguishes the return shape (structured, not narrative). However, it does not differentiate itself from the near-identical sibling luca_morning_report, leaving an agent unsure which of the two to pick.

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 line 'No model call; summarize client-side' tells the agent what to do with the result and that no LLM is invoked server-side, which is genuine usage guidance. But there is no explicit when-to-use vs alternatives (luca_morning_report, luca_review_queue_list, luca_insights_unread_count), so selection remains implied.

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