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demeet2k

Athena MCP Server

by demeet2k

athena_hug_plan

Create HUGINV execution packet for a registered implementation: validate input schema, freeze snapshot/context/input digest, return PLANNED only. Does not execute or invent QHUG semantics.

Instructions

Create HUGINV execution packet for registered implementation. Requires exactly io,au,fx,lm,er,st, validates registered input schema, freezes implementation snapshot/context/input digest and returns PLANNED only. It does not execute or invent QHUG semantics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorNo
contextNo
impl_idYes
argumentsYes
required_statusNo
Behavior5/5

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

With no annotations provided, the description carries the full burden and meets it: it discloses validation ('validates registered input schema'), state freezing ('freezes implementation snapshot/context/input digest'), return status ('returns PLANNED only'), and non-execution ('does not execute or invent QHUG semantics'). This provides rich behavioral detail beyond the structured schema.

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 three sentences long, with the main action front-loaded in the first sentence. Every sentence adds necessary information—requirements, behavior, and exclusions—with no redundancy or filler.

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

Completeness4/5

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

The description covers core behaviors: creation, validation, freezing, return status, and non-execution. However, it does not explain the optional parameters (actor, context, required_status) or the structure of the returned packet, which would be helpful given there is no output schema. The non-execution caveat is valuable but the tool's integration with the HUGINV workflow is only partially described.

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?

The schema has 0% description coverage, so the description must compensate. It mentions the required keys 'io,au,fx,lm,er,st' but gives no meaning for them, and it does not explain optional parameters like actor, context, or required_status. The only implicit parameter hint is 'for registered implementation' referring to impl_id, leaving most parameters semantically undocumented.

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 opens with 'Create HUGINV execution packet for registered implementation', which clearly specifies the verb (Create) and resource (HUGINV execution packet). It further distinguishes from related tools by stating 'It does not execute or invent QHUG semantics', separating it from execution tools like athena_hug_invocation.

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 context for when to use the tool: 'for registered implementation' and 'Requires exactly io,au,fx,lm,er,st' indicate prerequisites. The line 'It does not execute or invent QHUG semantics' tells the agent not to use this tool for execution, but it does not name a specific alternative, so it stops short of explicit when-not-to-use guidance.

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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