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demeet2k

Athena MCP Server

by demeet2k

athena_retrieval_compile

Compile a budgeted, coverage-aware retrieval decision from provenance candidates, treating unwitnessed measurements as UNKNOWN and optionally persisting the result.

Instructions

Compile and optionally persist a RAG.1 decision over supplied provenance candidates. Present measurements must be witnessed 0..1 packets; missing required measurements become UNKNOWN and measurement_plan. Selection is coverage-aware, budgeted, EQ1-safe and replayable. This tool does not claim it searched sources it was not given.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNo
actorNo
queryYes
persistNo
query_refYes
candidatesYes
eq_snapshotNo
equivalence_contextNo
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 of behavioral disclosure and does so richly. It reveals that present measurements must be witnessed, missing required measurements become UNKNOWN, selection is coverage-aware/budgeted/EQ1-safe/replayable, and the tool does not claim to have searched sources it was not given. This goes well beyond a basic functional statement.

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 dense sentences with no wasted words. It front-loads the core purpose, then adds behavioral constraints and a caveat. Every sentence contributes new information, making it appropriately sized for the tool's complexity.

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 is highly complex with 8 parameters, nested objects, no output schema, and no annotations. While the description covers high-level behavior and edge cases (missing measurements, replayability), it omits critical details such as return values, error conditions, and any parameter-specific explanations. The description is decent but incomplete for the complexity involved.

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 must compensate for the 8 parameters and nested objects. However, it only vaguely references 'persist' and 'candidates' without explaining any parameter specifics, such as query_ref, query structure, eq_snapshot, or equivalence_context. The description fails to add meaningful per-parameter semantics.

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 'Compile and optionally persist a RAG.1 decision over supplied provenance candidates.' This is a specific verb+resource construction that distinguishes it from sibling tools like athena_retrieval_get, athena_retrieval_recent, and athena_retrieval_replay. The scope is well-defined: it operates on supplied candidates, not on retrieval itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The usage context is implied through phrases like 'over supplied provenance candidates' and 'does not claim it searched sources it was not given,' which suggest using this tool when candidates are already available rather than for search. However, no explicit 'use when' or 'instead of X' guidance is provided, and no alternative tools are named.

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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