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kongen-labs

kongen-mcp

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by kongen-labs

transfer_score

Score a 7-dimensional signal vector against reference patterns to obtain pattern classification, confidence metrics, and supporting evidence.

Instructions

Score a 7-dimensional signal vector against reference patterns. Returns pattern classification, confidence, confidence adjustment, and supporting evidence. Costs 50 Kongen Tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
complexityYesPrimary signal dimension. Range [0, 1].
constraintYesCounterbalancing signal dimension. Range [0, 1].
boundaryYesBoundary sharpness. Range [0, 1].
coherenceYesMulti-scale consistency. Range [0, 1].
magnitudeYesOverall signal magnitude.
balanceYesPrimary signal ratio.
gradientYesSpatial gradient strength. Range [0, 1].
source_domainNoOriginating domain hint. Excludes same-domain patterns from evidence.
Behavior4/5

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

Since no annotations are provided, the description carries full burden. It discloses return values (pattern classification, confidence, adjustment, evidence) and token cost (50 Kongen Tokens). It also mentions that the optional parameter 'source_domain' excludes same-domain patterns. However, it does not explicitly state whether the operation has side effects or requires authentication, but as a scoring function it is likely safe.

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 extremely concise: two sentences covering purpose, return values, and token cost. Every word is meaningful and front-loaded. No fluff or repetition. It is well-structured for quick understanding.

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?

The tool has 8 parameters and no output schema. The description provides a high-level overview of output fields but lacks details on their structure or types. It covers the essential purpose and cost, but could be more complete given the complexity of the tool. It is adequate but not thorough.

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?

Schema description coverage is 100% with all parameters described in the JSON schema. The tool description adds no parameter-specific information beyond the schema. Since the schema fully documents parameters, a baseline score of 3 is appropriate.

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 tool's purpose: scoring a 7-dimensional signal vector against reference patterns. It uses a specific verb ('score') and specifies the resource ('7-dimensional signal vector'). The output is also listed: pattern classification, confidence, etc. This distinguishes it from siblings like 'score_prompt' which likely scores prompts, not signal vectors.

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?

No usage guidelines or comparisons to sibling tools are provided. The description does not indicate when to use this tool over alternatives like 'score_prompt', nor does it specify prerequisites or context. The implied usage is for signal vector scoring, but no explicit guidance is given.

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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