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SetLuca

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by setluca

Get the morning digest

luca_morning_report
Read-onlyIdempotent

Retrieve a coach's last-24-hour review-queue digest, listing queued drafts with status and confidence plus status counts for daily triage.

Instructions

Return the coach's structured last-24h review-queue digest: queued drafts with status and confidence, plus counts by status. No model call — summarize it client-side. Example: call with {} at the start of the day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdNoOptional Luca workspace id override.
workspaceSlugNoOptional Luca workspace slug override.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
provenanceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds real behavioral value beyond that: no model call is made, the output is structured data meant to be summarized client-side, and the window is fixed at the last 24h.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with what is returned, then the no-model-call/summarize instruction, then a usage example. Nothing is padding; each sentence carries a distinct instruction.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 shape need not be restated, and annotations cover the safety profile. What remains — window, contents, no-LLM behavior, and default invocation — is all present, leaving nothing an agent needs to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so workspaceId and workspaceSlug are already documented; the baseline would be 3. The description adds the meaningful operational fact that an empty object is valid, telling the agent both params are true overrides with a default workspace resolution.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource ('Return the coach's structured last-24h review-queue digest') plus the payload contents (queued drafts with status and confidence, counts by status). This is enough to separate it in spirit from item-level siblings like luca_review_queue_list, but no sibling is named explicitly, so differentiation is inferred rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear usage context ('call with {} at the start of the day') and implicitly routes the agent away from re-querying by saying to summarize client-side. There is no explicit when-not guidance or named alternative (e.g. luca_review_queue_list for raw items), so it stops short of a 5.

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

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