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Glama

Recommend

oi.recommend
Read-onlyIdempotent

Recommend the best Oi Context or Workflow for a prompt. Use this when the user asks oi recommend or wants help choosing the most suitable reusable setup before running it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe user's task or request to match against installed Contexts and Workflows.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYes
contextNo
workflowNo
contextIdNo
confidenceYes
workflowIdNo
contextNameNo
workflowNameNo
leadContextIdNo
resolutionModeNo
leadContextNameNo
routedImplicitlyNo
resolvedEntityTypeYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The phrase 'before running it' clarifies that the tool recommends rather than executes, which is meaningful behavioral context. Annotations already indicate readOnly, idempotent, and non-destructive behavior, so the description supplements rather than contradicts them.

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?

Two concise sentences: the first states the core function and the second gives the triggering usage. There is no filler or repetitive phrasing.

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?

For a simple, single-parameter, read-only recommendation tool, the description is complete. The output schema covers return details, annotations cover safety, and the description provides purpose and usage context.

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 description coverage is 100%, with the prompt parameter already documented as the task/request to match against installed Contexts and Workflows. The tool description adds little beyond that, so it meets the baseline without significantly enriching parameter meaning.

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?

Description states a specific action ('Recommend') and a specific resource ('best Oi Context or Workflow for a prompt'). It is clear about what the tool does, though it does not explicitly distinguish itself from related search/use siblings such as oi.contexts.search or oi.workflows.use.

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?

The description gives a direct when-to-use condition: when the user asks 'oi recommend' or wants help choosing the most suitable reusable setup. It does not list when-not-to-use or explicitly name alternatives, but the intended context is clear.

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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TDQS

A3.5/5.0
Disambiguation4/5

Resource prefixes (contexts, skills, guardrails, workflows, connections) make most tools clearly distinct, and parallel lifecycle verbs are scoped by resource name. The main ambiguity is within the guardrails publish/release/unpublish lifecycle and between brain.save-feedback, contexts.save-draft-feedback, and the two report tools, though detailed descriptions mostly resolve it.

Naming Consistency4/5

Tools overwhelmingly follow an oi.<resource>.<verb> snake_case pattern, with create/get/list/update/use repeated consistently across resource types. Deviations include resource-less oi.recommend, noun-style oi.auth.whoami, and inconsistent release handling (separate guardrails.release vs action=release on contexts/skills update).

Tool Count2/5

38 tools is too many for a single server, mainly because the same lifecycle pattern is repeated across Contexts, Skills, Guardrails, and Workflows. Each tool may be individually justifiable, but the set feels bloated and could benefit from consolidation or splitting into per-resource servers.

Completeness3/5

CRUD coverage is uneven: Guardrails have create/update/delete/list/get plus publish/unpublish/release, while Contexts, Skills, and Workflows lack any delete or archive tool, and Brain has only save-feedback with no read/update/delete path. Connections and auth are read/use-only, which may be intentional but leaves management actions absent.