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Get Recommendation

get_recommendation
Read-onlyIdempotent

One recommendation brief and saved lifecycle: board stage, movement, origin, review flag, dates, grades, scope, baseline measurement and seed. Complete text; evidence and linked prompts each default to 10/max 20 with independent evidenceNextCursor/promptsNextCursor. Continue via evidenceCursor/promptCursor with the same subject and recommendation. Evidence includes claim/prompt/Scan IDs from its actual source; historical same-subject evidence is allowed. Missing recommendations are not_found. Restart after edits; these are live pages. Actions/notes use their own list tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteIdYesSite or topic ID from list_sites_and_topics. Check subjectKind; topics support manual baseline scans.
promptLimitNo
promptCursorNo
evidenceLimitNo
evidenceCursorNo
recommendationIdYesA recommendationId from get_recommendations.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedYes
briefYes
scopeYes
titleYes
topicYes
effortYes
impactYes
intentYes
originYes
statusYes
promptsYes
readyAtYes
summaryYes
evidenceYes
movementYes
questionYes
standingYes
createdAtYes
updatedAtYes
approvedAtYes
archivedAtYes
confidenceYes
confirmedAtYes
needsReviewYes
publishedAtYes
raisedScanIdYes
archiveReasonYes
targetStandingYes
recommendationIdYes
promptsNextCursorYes
evidenceNextCursorYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial context: default page size 10 with a max of 20, independent evidence/prompt cursors, the not_found behavior for missing recommendations, that historical same-subject evidence is permitted, and that these are live pages requiring a restart after edits. This is rich behavioral disclosure well beyond the structured fields.

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?

Front-loaded and information-dense with no filler sentences; every clause conveys a distinct behavior. The telegraphic, list-like phrasing makes it slightly harder to parse but wastes 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?

For a two-key read tool with output schema, it covers pagination, continuation, error behavior, and cross-tool routing. It redundantly enumerates return fields that the output schema already provides, but no critical calling information is missing.

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 only 33%, so the description carries most of the load for the four cursor/limit parameters, and it does explain the 10-default/20-max limits and the cursor-continuation contract. Minor naming drift ('promptsNextCursor' for the response vs 'promptCursor' to continue) keeps it from a 5.

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?

The description states a specific resource and scope: fetching a single recommendation's brief and saved lifecycle, enumerating the fields it carries (board stage, movement, grades, scope, etc.). It implies singularity and thus contrasts with the sibling get_recommendations, though it never names that sibling explicitly, so it falls short of a top score.

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

Usage Guidelines3/5

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

It gives partial routing ('Actions/notes use their own list tools') and continuation rules for cursors, but never states explicitly when to call this versus get_recommendations. Usage is implied by the singular framing rather than spelled out.

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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