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demeet2k

Athena MCP Server

by demeet2k

athena_record_holonomy

Persist a measured closed coordinate-loop observation, capturing start, returned state, defect, metric, and provenance event.

Instructions

Persist a measured closed coordinate-loop observation H_gamma with start, returned state, defect, metric and provenance event.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorNo
routeYes
startYes
defectYes
metricNo
statusNo
returnedYes
subject_idYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that the tool persists data, but it does not mention return values, idempotency, validation rules, failure modes, or required authorization—important for a write operation.

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 a single sentence with the action and object front-loaded, making it compact and easy to scan. However, the dense jargon ('H_gamma', 'provenance event') and a reference to a field not present in the schema reduce its structural effectiveness slightly.

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?

Given the tool has 8 parameters, 5 required, no annotations, no output schema, and empty schema definitions for several properties, this description is insufficient. It does not explain key parameters, return behavior, or persist semantics, leaving an agent unable to confidently construct a valid invocation.

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%, so the description should compensate heavily. It names some fields ('start', 'returned state', 'defect', 'metric') and adds a 'provenance event' concept, but it omits required fields like subject_id and route, and the schema has no 'provenance_event' property, making the mapping confusing and incomplete.

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 uses a specific verb 'Persist' and a precise resource ('measured closed coordinate-loop observation H_gamma'), clearly stating what the tool does. This distinguishes it from sibling record-style tools by naming the exact domain object and key persisted fields.

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 guidance is given about when to use this tool versus alternatives such as athena_commit_delta or athena_register. There are no context cues, exclusions, or prerequisite conditions, so an agent receives no decision support for selecting this tool.

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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