memory_ontology_propose_entityPropose a typed ontology entity (active immediately).
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | Alias for kind_name | |
| name | Yes | Display name for the entity | |
| agent | No | Override agent identity | |
| kind_name | No | Registered object kind, e.g. Person or Project | |
| properties | No | Optional JSON properties matching the kind schema |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It discloses one meaningful trait — the entity is 'active immediately', implying a direct creation with no approval or staging step — which is more than a bare verb. However, it says nothing about prerequisites (e.g., whether the kind must already be registered), idempotency, reversion, or failure behavior when the kind does not exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single eight-word sentence that is front-loaded and contains no wasted words; the parenthetical earns its place by disambiguating the semantics of 'propose'. It is terse to the point of under-specification, but that deficiency is properly penalized in other dimensions rather than here.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The existence of an output schema and 100% parameter coverage lowers the burden, and the tool's shape is simple (flat, 1 required parameter, no enums). Even so, an agent cannot determine from this description when to select it over memory_remember or memory_entity_view, or whether the named kind must already exist in the ontology. For a tool in a crowded sub-family, this is minimally viable but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 even with no parameter detail in the description. The word 'typed' reinforces the role of kind/kind_name and implies properties should conform to the kind schema, marginally reinforcing the schema's 'Registered object kind' note. It adds no syntax, defaults, or format guidance beyond what the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Propose') and resource ('typed ontology entity'), and the parenthetical '(active immediately)' clarifies that the entity takes effect at once rather than requiring approval. It is distinguishable from sibling tools like memory_ontology_list, memory_ontology_merge_entities, and memory_ontology_rekind_entity, though it does not name them. It stops short of 5 because 'propose' could still be misread by an agent unfamiliar with the immediate-activation parenthetical.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as memory_remember, memory_entity_view, or the other memory_ontology_* siblings. With a sibling list of 90+ tools and no when-to-use or when-not-to-use conditions, an agent is left to infer applicability. This is a clear gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
With 104 tools across many domains (memory, work, projects, files, agents, context, strategic, ontology), the use of clear prefixes (memory_, work_, project_, file_, agent_run_, context_) makes most tools distinct. However, there are some potential confusions between memory_session_* vs memory_state_*, and memory_recall vs memory_think vs memory_assemble_context, though descriptions clarify their specific purposes. Aliases like memory_playbook_get for memory_procedure_get are explicit and reduce ambiguity.
Tool names follow a highly consistent pattern: prefix_domain_action (e.g., file_create, work_update, memory_recall, agent_run_start). All use snake_case, with verbs consistently placed after the domain prefix. Even less common tools like account_brief and attention_snapshot fit the overall naming scheme, making the set predictable and easy to navigate.
At 104 tools, this is an exceptionally large surface area, far exceeding the 25+ threshold that feels heavy. However, the server covers an extensive domain (organizational memory, work management, project tracking, file sharing, agent orchestration, and strategic planning), which justifies a large count. Still, the sheer number may overwhelm agents, and some tools could be consolidated (e.g., many memory_session_* and memory_state_* variants).
The tool surface is remarkably complete for its stated purpose, covering CRUD operations for files, work items, projects, and memory, plus lifecycle management for agents, sessions, and strategic plans. Minor gaps exist (e.g., no direct memory_item_get by ID, no section removal in projects), but agents can work around these using existing tools like memory_recall or work_create with parent_id. Overall, the set minimizes dead ends.