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memory_agent_ensure

Get-or-create this org's ontology Agent + shared memory profile.

Harness agents slug to agent-<label>. Cloud agents slug to agent-<cursor_agent_id>. Other agents read the profile with memory_agent_get or memory_entity_view.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoHarness label (cursor, grok, dispatcher). Omit for the caller.
agentNoOverride agent attribution label
modelNoCursor model id when known (composer-2.5, auto-smart, …)
harnessNoHarness type that owns this agent (cursor, grok-bot, …)
runtimeNoharness (MCP client) or cloud (Cursor cloud agent)
spawned_byNoParent Agent slug or label (dispatcher that spawned this cloud agent)
cursor_agent_idNoCursor cloud agent id (bc-…). Sets runtime=cloud when provided.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It openly states the side effect (get-or-create), the org scope, and the exact slug derivation for harness vs. cloud agents. It does not say whether existing profiles are silently returned or updated, but 'Get-or-create' communicates the core non-destructive intent.

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?

The description is compact and front-loaded with the most important information: the operation and its resource. The slugging rules and read-alternative pointer are each one clause with no filler or repetition.

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?

Given the output schema handles return values and the schema covers all 7 optional parameters, the description is largely complete. It misses a small but useful pointer to memory_agent_set for explicit updates, but the get-or-create semantics and read alternatives cover the main decision paths.

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 description coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining how parameters map to the agent slug (name to agent-<label>, cursor_agent_id to agent-<cursor_agent_id>), which is not derivable from the individual parameter descriptions alone.

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?

The description opens with a precise verb phrase 'Get-or-create' and a specific resource ('this org's ontology Agent + shared memory profile'), so an agent knows exactly what the tool does. The slugging convention distinguishes it from read-only siblings like memory_agent_get and memory_entity_view, and the 'ensure' semantics are immediately clear.

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 actionable context: use this tool to get-or-create an agent profile, and read the profile with memory_agent_get or memory_entity_view. It does not explicitly say when to use memory_agent_set or memory_agent_list instead, but the get-or-create framing and named read alternatives provide decent routing guidance.

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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