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Glama

save_knowledge_edges

Persist knowledge edges after validating the DAG; reject invalid graphs to maintain learning path integrity.

Instructions

Persist knowledge edges. The DAG is validated first and rejected if invalid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
edgesYes
request_idNo
session_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It does disclose a meaningful trait: the DAG is validated first and invalid DAGs are rejected. However, it omits mutation semantics (overwrite vs merge), success/error behavior, and session requirements, leaving the persistence behavior only partly transparent.

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 two tight sentences with no filler, and the main action is front-loaded. It earns its brevity, though it is slightly under-specified for a persistence tool with no schema-level parameter descriptions.

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, no annotations, and 0% schema description coverage, the description is incomplete. It does not explain what an edge should look like, how session_id is used, what request_id is for, or how this relates to validate_knowledge_dag and save_knowledge_nodes. An agent would have to infer too much to call it reliably.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds only that 'edges' are knowledge edges forming a DAG, but does not define the edge shape, required fields, or the semantics of session_id and request_id. This is minimal compensation for an otherwise undocumented parameter set.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Persist') and resource ('knowledge edges'), and adds a distinguishing detail by noting the DAG is validated first. It is clear enough to separate from get_knowledge_edges and validate_knowledge_dag, though it does not explicitly contrast with save_knowledge_nodes.

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 guidance is given about when to use this tool versus save_knowledge_nodes, validate_knowledge_dag, or get_knowledge_edges. The only usage signal is the action itself, with no scenarios, exclusions, or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.