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Enhanced Knowledge Graph Memory Server

detect_causal_cycles

Detect cycles in causal subgraphs rooted at a given seed, including cycles formed by prevents and enables relationships.

Instructions

3B.6 — Detect cycles in the causal subgraph rooted at seed. CAVEAT: treats prevents as a directed edge, not as logical negation — prevents+enables triangles ARE flagged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedYes
maxDepthNo
Behavior3/5

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

With no annotations, the description must carry the full burden. It discloses the key behavioral detail about prevents edges causing triangles to be flagged, but does not mention edge cases (e.g., seed not found), performance, or side effects.

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 concise: one sentence plus a caveat. The caveat is important and front-loaded. No wasted words.

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?

Without output schema and with no parameter explanations, the description is incomplete. An agent lacks guidance on inputs and expected outputs.

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

Parameters1/5

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

Schema description coverage is 0% and the description does not explain either parameter (seed or maxDepth). It adds no meaning beyond the schema, failing to compensate for the low coverage.

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 clearly states 'Detect cycles in the causal subgraph rooted at seed' with a specific verb and resource. It distinguishes from siblings like find_causes/find_effects by focusing on cycles, though it could be clearer about the cycle type (e.g., directed cycles).

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 caveat about prevents edges hints at an important nuance but does not explicitly state when to use this tool over alternatives or when to avoid it. No direct usage guidance is provided.

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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