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DanNsk

Multi-Memory MCP Server

by DanNsk

delete_observations

Remove specific observations from your knowledge graph memory by ID or by entity identifier, observation type, and source.

Instructions

Delete specific observations. Specify by observation id OR by entity identifier + observationType + source.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoMemory category. Defaults to 'default'
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 but only states that it deletes observations. It does not disclose whether deletion is irreversible, requires permissions, or has side effects (e.g., cascade deletions). The deletion behavior is implied but not elaborated.

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 extremely concise (two sentences, 16 words), front-loads the purpose, and has no wasted content. Every word is necessary and informative.

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 no output schema and no annotations, the description should cover behavior like return values, error handling, and side effects. It does not address what happens if observations are not found, whether multiple deletions are atomic, or if any prerequisites exist. The description is incomplete for a deletion tool.

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 50%, but the description adds value by concisely summarizing the two identification patterns: 'by observation id OR by entity identifier + observationType + source.' This clarifies the relationship between parameters beyond what individual field descriptions provide. However, the schema already has comparable descriptions for each parameter, so the added value is moderate.

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 clearly states the tool deletes observations and specifies two identification methods (by observation ID or by entity identifier + observationType + source). This differentiates it from sibling tools like delete_entities and delete_relations, which target different resources.

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 explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or conditions for use. The agent must infer usage based on the resource name ('observations' vs siblings).

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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