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putervision

agent-reasoning-mcp

by putervision

set_utility_weights

Configure and activate utility weights for aggression, caution, greed, exploration, and cooperation to control an agent's strategic decision-making.

Instructions

Configure and activate multi-attribute utility weights (aggression, caution, greed, exploration, cooperation).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
actionYes
projectNo
weightsNo
is_activeNo
descriptionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations provided, the description alone carries the burden of behavioral disclosure. It hints at mutation ('configure', 'activate') but never says whether activation is immediate, persistent, reversible, or what side effects occur on existing behavior. The read actions (get/list) are not disclosed at all through the description, even though they are part of the schema.

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 definition is a single front-loaded sentence that communicates the core action and the domain of the weights. It avoids fluff and is easy to skim. Adding a pruning phrase such as 'get/list' or a usage hint would make it longer but not necessarily wordier, so it is adequate for its length.

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?

The tool has six parameters, a free-form nested object, no output schema, and no annotations. A one-sentence description leaves out essential decision points: what each action does, how 'weights' values are represented (ranges, types), what project/name/is_active/description are for, and what the tool returns. This is materially incomplete for an agent selecting and invoking the tool safely.

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 coverage is 0%, so the description must add meaning. It does add the semantic content of the 'weights' object by listing its five attributes, which is genuinely useful. However, the other five parameters (name, project, is_active, description, and the action semantics beyond the enum) are left undocumented, so a fair fraction of the parameters are still ambiguous.

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 verb ('configure and activate') and a clear resource ('multi-attribute utility weights') with a concrete list of attributes. It distinguishes itself from the decision-making siblings like set_goal and assess_risk. However, it only mentions two of the four actions in the enum; the 'get' and 'list' actions are omitted, so the stated purpose under-represents the actual scope.

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 explicit guidance on when to use this tool versus alternatives. Nothing explains context such as 'when your utility profile needs updating' or rules out per-decision tweaking versus global strategy. The attribute list is the only subtle hint, leaving the agent to infer the purpose.

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