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best_next_steps

Routing recommendation: the strongest next cognitive steps from a given node, by learned edge weight and trust.

Input Schema

NameRequiredDescriptionDefault
limitNo
agent_idYes
from_nodeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior2/5

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

Annotations declare readOnlyHint=false and idempotentHint=false, meaning the call may change state, but the description calls it a 'recommendation' and never explains what side effect occurs or whether the learned weights are updated by the call itself. The only behavioral context added is the ranking mechanism, which does not resolve the read-vs-write ambiguity the annotations raise.

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?

A single front-loaded sentence with no filler; the ranking basis is stated up front. It is efficient but borders on under-specification rather than earning full marks for structure.

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?

An output schema exists so return values need not be described, but with 0% parameter documentation and no annotation-level explanation of the non-read-only behavior, one line is not enough for a 3-parameter tool in a dense routing/graph sibling set.

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% across three parameters, so the description must compensate and largely does not. 'from a given node' loosely maps to from_node, but agent_id and limit are never mentioned, and nothing explains what a node represents or how limit interacts with ranking.

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 names a specific resource (next cognitive steps from a given node) and the ranking basis (learned edge weight and trust), which is more than a restatement of the name. It stops short of differentiating itself from the obvious sibling route_task, so an agent must infer the recommend-vs-execute distinction.

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?

There is no when-to-use guidance, no prerequisites, and no mention of route_task or record_route_outcome, which are the natural alternatives in this sibling set. The agent is left to infer that this is a planning/consultation call rather than an execution call.

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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