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SetLuca

SetLuca

Official
by setluca
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

List knowledge suggestions

luca_knowledge_suggestions
Read-onlyIdempotent

List profile changes proposed from the coach's own knowledge sources, each with the excerpt it was drawn from and the value it would replace.

Instructions

List profile changes proposed from the coach's own knowledge sources, each with the excerpt it was drawn from and the value it would replace. Approving one is app-only, so a person checks each change before it reaches the profile; this lists them and luca_knowledge_reject_suggestion turns one down.

Luca operation: GET /api/knowledge/suggestions Required scopes: knowledge:read Required OAuth scope: luca:read; data sensitivity: redacted Does not require idempotency. Use workspaceId or workspaceSlug to override the default workspace configured by environment.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "luca_knowledge_suggestions"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNo
workspaceIdNoOptional Luca workspace id override.
workspaceSlugNoOptional Luca workspace slug override.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.1/5.0
Behavior4/5

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

Goes beyond the readOnly/idempotent annotations by disclosing required scopes (knowledge:read, luca:read), redacted data sensitivity, and the fact that approval cannot happen here. Minor tension with idempotentHint=true in the line 'Does not require idempotency', though that reads as 'no idempotency key needed' rather than a contradiction.

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

Conciseness4/5

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

The prose is front-loaded and efficient: what it returns, then the approval/rejection routing. The trailing metadata block (operation, scopes, idempotency, workspace override) is boilerplate, and the workspace sentence duplicates the schema descriptions, costing a little space.

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

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values needn't be spelled out, and the description still summarises item content (excerpt plus replaced value). The main omission is the status filter and any pagination/volume expectations for a list that could be long.

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

Parameters3/5

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

Schema coverage is 67%: workspaceId and workspaceSlug are already documented in the schema, and the description only restates the override behaviour. The undocumented piece — the nested query.status enum (pending/approved/rejected) — is never mentioned, so an agent gets no guidance on filtering by review state.

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

Purpose5/5

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

States a specific verb and resource — listing profile changes proposed from the coach's own knowledge sources — and adds the shape of each item (excerpt, value to be replaced). It names the adjacent tools (luca_knowledge_reject_suggestion, knowledge sources) so an agent can place it in the workflow without opening schemas.

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?

Explains the review context: approval is app-only, so this tool surfaces items for a human, and rejection is routed to luca_knowledge_reject_suggestion. That is clear when-to-use and a named alternative, but it gives no exclusions against neighbouring list tools such as luca_learning_proposals_list or luca_knowledge_sources_list.

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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