Add a subject-predicate-object triple to the knowledge graph to build persistent, local-first AI memory across sessions, with optional confidence and validity dates.
Add a triple to the knowledge graph.
| Name | Required | Description | Default |
|---|---|---|---|
| object | Yes | ||
| subject | Yes | ||
| predicate | Yes | ||
| confidence | No | ||
| valid_from | No | ||
| valid_until | No |
Changes observed during successful MCP inspections.
v1.7.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It says nothing about permissions, idempotency, validation, side effects, or how the graph is modified—only that a triple is added.
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 single sentence is concise and front-loaded, but it is under-specified for a 6-parameter mutation tool. It is too terse to be considered appropriately sized given the complexity.
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?
With no annotations, no output schema, and six undocumented parameters, the description is completely inadequate for an agent to invoke the tool correctly. It omits required context about behavior, parameters, and usage.
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?
The schema has 6 parameters with 0% description coverage, and the description does not mention any of them. It fails to explain subject, predicate, object, or the optional confidence, valid_from, and valid_until fields.
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?
States a clear verb ('Add') and resource ('triple to the knowledge graph'). It distinguishes the operation from read-only siblings like engram_kg_query, but does not explicitly differentiate from other mutation tools such as engram_kg_invalidate or engram_correct.
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?
Provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, context, or sibling tools like engram_kg_query or engram_kg_invalidate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.