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connect

Link two memories to build a knowledge graph, connecting decisions to rationale or patterns to examples.

Instructions

Create a relationship between two memories. Build knowledge graphs by linking decisions to rationale, patterns to examples, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notesNoOptional notes about the relationship
source_idYesFirst memory ID
target_idYesSecond memory ID
relationshipNoType: RELATED_TO, LEADS_TO, SUPPORTS, CONTRADICTS, DEPENDS_ONRELATED_TO
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses a mutation operation ('create') but provides no details on side effects, required existence of memory IDs, relationship directionality, or whether existing relationships are replaced. This is a significant gap for a write operation.

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 two sentences, front-loaded with the core action, and contains zero wasted words. Every part earns its place, though the trailing 'etc.' is slightly vague, but acceptable.

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

Completeness3/5

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

While the tool is relatively simple and the schema is rich, the description lacks behavioral details such as return values, idempotency, or what happens on conflict. Given the absence of annotations and output schema, a bit more contextual disclosure would help, but it's not severely deficient.

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 input schema covers all four parameters with descriptions (100% coverage), so the schema does the heavy lifting. The description adds no parameter-specific guidance, but the baseline of 3 is appropriate as the schema is sufficient.

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 clearly states the action ('create a relationship') and the resource ('between two memories'). It distinguishes itself from siblings like remember and recall by focusing on linking, not storing or retrieving. The additional 'build knowledge graphs' phrase reinforces its unique role.

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 provides clear usage context with concrete examples ('linking decisions to rationale, patterns to examples'), implying when to use this tool. However, it does not explicitly state when not to use it or offer alternatives to consider, so it lacks exclusions.

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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