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add_assertion

Create a directed relationship between entities in a code knowledge graph, specifying relation type, confidence, and domain evidence.

Instructions

Create a precise edge between two nodes in the knowledge graph.

Use this when you need exact control over the graph structure:

  • Specific relation type between two entities

  • Confidence level on an assertion

  • Domain scoping

Both "from" and "to" become nodes if they don't exist yet.

Example: add_assertion(from="Grafema", relation="uses", to="RFDB", context="RFDB is the storage engine for code graphs", confidence=1.0)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fromYesSource entity name or ID
relationYesRelation type for the edge
toYesTarget entity name or ID
contextNoAdditional context or evidence for this assertion
confidenceNoConfidence level 0-1
domainNoKnowledge domain this assertion belongs to
Behavior4/5

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

Discloses that nodes are created if absent, a key side effect. No annotations present, so description carries burden. However, it does not mention idempotency or conflict behavior.

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?

Three short paragraphs plus an example, all front-loaded with purpose. No unnecessary words; every sentence adds value.

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

Completeness4/5

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

Covers purpose, usage, key behavior, and example. Lacks return value description, but given tool simplicity and no output schema, it is nearly complete.

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 coverage is 100%, so baseline 3. Description adds little beyond schema; the example gives context but does not explain parameter constraints or relationships.

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?

Description states specific verb 'Create' and resource 'edge between two nodes in the knowledge graph', clearly distinguishing from siblings like delete_assertion and update_assertion.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit use cases (specific relation, confidence, domain) and an example, but lacks explicit when-not-to-use or comparison with alternatives like bulk imports.

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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