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akb_link

Create a typed relation between two resources in the same vault to represent dependencies, references, attachments, or implementations, linking documents, tables, and files.

Instructions

Create a relation between any two resources (documents, tables, files). Source and target are AKB URIs in the same vault. Relation types: depends_on, related_to, implements, references, attached_to, derived_from. Example: link a design doc to its data table, or attach a diagram file to a spec.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesSource resource URI (e.g. akb://vault/doc/specs/api.md)
targetYesTarget resource URI (e.g. akb://vault/table/experiments)
relationYesRelation type
_vault_skill_ackNoOpaque acknowledgement returned as vault_skill.ack_token. After applying that guide, retry the unchanged operation with this value. The bundled proxy supplies it automatically.

Schema Changelog

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

  1. Changed1 schema field changedv2.0.14
    • addedInput schema / properties / _vault_skill_ack
      Added value: +{
      +  "description": "Opaque acknowledgement returned as vault_skill.ack_token. After applying that guide, retry the unchanged operation with this value. The bundled proxy supplies it automatically.",
      +  "maxLength": 128,
      +  "type": "string"
      +}
  2. Addedv2.0.4
  3. Removedv2.0.1
  4. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations present, the description carries the behavioral disclosure burden. It clearly states that this creates a relation, restricts source and target to AKB URIs in the same vault, and enumerates valid relation types. However, it does not disclose important behavior such as whether duplicate relations are rejected or replaced, whether relations are directional, or what the response/return value looks like.

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?

The description is compact and front-loaded with the core action and purpose. Every sentence earns its place: the operation, constraints, allowed relation types, and a clarifying example are all included without redundancy.

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 relatively simple create-relation tool with full schema coverage, the description is complete enough for an agent to invoke it correctly. It explains the core behavior, constraints, and typical use cases. The only notable gap is the absence of return-value or post-condition details, but this is not critical given the simplicity of the operation.

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?

The schema already documents all parameters with 100% coverage, so the baseline is 3. The description adds useful examples of source/target URIs and relation types, but it does not meaningfully enrich the semantics of individual parameters beyond what the schema already provides.

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 names a specific action ('Create a relation'), a concrete resource domain ('between any two resources: documents, tables, files'), and the supported relation types. This cleanly distinguishes it from read-only sibling tools like akb_relations and the inverse operation akb_unlink.

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?

The description makes the intended use clear with concrete examples, such as linking a design doc to its data table or attaching a diagram to a spec. It does not explicitly state when not to use it or name alternatives, but the context is sufficiently clear for an agent to decide when this is the right tool.

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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