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Keep a study insight in Ledger

prism_insights_promote

Promotes an analysis theme (or, with no themeId, the analysis summary) into the workspace's Ledger as a belief, carrying the supporting verbatims as evidence with links back to the study. THE step that turns a finding into workspace memory — use when the user says an insight matters. May return needs_confirmation.

Input Schema

NameRequiredDescriptionDefault
studyIdYes
themeIdNoA theme id from prism_studies_get; omit for the summary.
workspaceNoWorkspace slug. Personal tokens with no default workspace MUST pass this; tokens with a default can override per call. Ignored for workspace API keys.
approvalIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare this as a non-readonly, non-destructive, closed-world write, so the bar is lower; the description still adds real value by disclosing that supporting verbatims are carried across as evidence with links back to the study, and that the call may return `needs_confirmation`. It does not explain what happens on that confirmation path, which keeps it out of the top band.

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?

Three tight sentences, front-loaded with the core action and destination before the nuance. The em-dash flourish ("THE step that turns a finding into workspace memory") is rhetorical rather than informational, but it is brief enough not to cost readability.

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

Completeness3/5

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

For a 4-parameter mutation with no output schema and only 50% schema coverage, the description covers the main flow and the confirmation signal but leaves the approvalId/confirmation round-trip and the relationship to the ledger_entries_* siblings unexplained. Adequate, with identifiable gaps.

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 50%, so the description must compensate, and it partially does: it explains the themeId-vs-summary branch that the schema leaves implicit. However, studyId and approvalId carry no description in either place, and approvalId is plausibly the key to the `needs_confirmation` behavior the description mentions but never connects.

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 precise verb (promotes) and resource (an analysis theme, or the analysis summary by default) and the destination (workspace Ledger as a belief), including what travels with it (supporting verbatims as evidence). An agent can distinguish this from ledger_entries_create or prism_studies_analyze without opening any schema.

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?

"use when the user says an insight matters" gives a concrete trigger condition, and the parenthetical about omitting themeId clarifies the branch between theme-level and summary-level promotion. It stops short of naming an alternative tool (e.g. ledger_entries_create) or a when-not condition, so it is clear context without exclusion.

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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