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add_observations

Append observations to existing entities in your knowledge graph, with options to set strength, confidence, and metadata for each observation.

Instructions

Add new observations to existing entities in your Memento MCP knowledge graph memory

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
observationsYes
strengthNoDefault strength value (0.0 to 1.0) for all observations
confidenceNoDefault confidence level (0.0 to 1.0) for all observations
metadataNoDefault metadata for all observations
Behavior2/5

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

With no annotations, the description must disclose behavior but only states 'add new observations'. It does not specify what happens if the entity does not exist, whether observations are appended or overwritten, or any other side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no fluff, but it omits important context. It is concise but not optimally structured with key usage info.

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 nested object structure and multiple parameters, the description is too sparse. It lacks explanation of relationships between observations and entities, and no output schema is provided to compensate.

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 75%, so the schema already explains most parameters. The description adds no further semantic value beyond the tool name, so a baseline score of 3 is appropriate.

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 uses a specific verb-resource pair ('Add new observations to existing entities') and clearly distinguishes from sibling tools like 'create_entities' or 'delete_observations'.

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?

No information is provided about when to use this tool versus alternatives (e.g., updating entities directly). No prerequisites or exclusions are mentioned.

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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