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3lehr
by 3lehr

knowledge_relation_add

Add a validated, evidence-backed knowledge edge between existing node IDs, checking scope, confidence, and duplicates to prevent ungrounded inferred links.

Instructions

Create one explicit evidenced knowledge edge between existing node IDs/paths. Never infers links from tags or text; validates endpoints, scope, type, confidence, and duplicate edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorNoCalling agent identity; else BEGOD_KNOWLEDGE_ACTOR or unknown
modelNoCalling model; else BEGOD_KNOWLEDGE_MODEL or unknown
scopeNoall or project; scoped calls permit shared + projectall
sourceNoSource artifact path/ID
weightNo
sessionNoStable session ID; else BEGOD_KNOWLEDGE_SESSION or unknown
evidenceYesWhy this edge is true; cite the decision/source
confidenceNo
source_nodeYesExisting source node ID or path
target_nodeYesExisting target node ID or path
relation_typeYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the disclosure burden and does well: it states the operation creates exactly one edge, requires existing endpoints, never infers links from tags/text, and validates scope, type, confidence, and duplicates. It does not cover authentication, response format, or failure behavior, but the core mutation semantics and validation constraints are disclosed.

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?

One dense sentence front-loads the primary purpose, then adds two high-value constraints without filler. Every clause earns its place.

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?

For a create-edge tool with no output schema, the description covers purpose, endpoint existence requirement, evidence requirement, and validation behavior, which is the core calling contract. It omits explicit return/error semantics and usage alternatives, but the parameter schema complements it well.

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 73%, and the schema already describes most parameters; the description adds the important contextual point that source_node/target_node must be existing IDs or paths and that edges are explicit and evidenced. It does not name or explain all optional parameters, but the schema handles that burden.

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 ('Create') and a precise resource ('one explicit evidenced knowledge edge'), with clear scope: only existing node IDs or paths. This distinguishes it from knowledge_relation_update/remove/list and from knowledge_add, so an agent can identify it without opening the schema.

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

Usage Guidelines3/5

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

The description implies its use case: add an edge between already-existing nodes when evidence is present, and never for inference-based linking. It does not explicitly name alternatives or state when not to use it, though sibling names make some of this inferable.

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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