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grizzlypeaksoftware

Memory MCP Server

delete_observations

Remove specific observations from entities in the knowledge graph stored on the Memory MCP Server. Specify entity names and observations to delete for precise data management.

Instructions

Delete specific observations from entities in the knowledge graph

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deletionsYes
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It implies a destructive mutation ('Delete') but lacks details on permissions, reversibility, side effects, or error handling. This is inadequate for a deletion tool with zero annotation coverage.

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 a single, efficient sentence with no wasted words. It's appropriately sized and front-loaded, directly stating the core action without unnecessary elaboration.

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

Completeness2/5

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

Given the tool's destructive nature, lack of annotations, no output schema, and 0% schema coverage, the description is incomplete. It fails to address critical aspects like confirmation prompts, impact on graph integrity, or response format, leaving significant gaps for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'specific observations' and 'entities in the knowledge graph', but doesn't explain the structure of 'deletions' array, what 'entityName' refers to, or how 'observations' are identified. This adds minimal value beyond the schema.

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 clearly states the verb ('Delete') and resource ('observations from entities in the knowledge graph'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'delete_entities' or 'delete_relations', which would require more specific language about scope.

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

Usage Guidelines2/5

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 like 'delete_entities' or 'delete_relations', nor does it mention prerequisites or context. It merely states what the tool does without indicating appropriate scenarios or exclusions.

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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