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compile_uai_context

Compile canonical project truth into a versioned UAI/1 execution packet with a semantic hash and savings metrics, enabling verifiable, cost-aware AI execution across multi-agent workflows.

Instructions

Compile canonical MangoMe truth into a versioned compact UAI/1 execution packet with semantic hash and savings metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slice_idNo
family_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.2

TDQS

C2.9/5.0
Behavior3/5

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

There are no annotations, so the description carries the full burden. It does disclose meaningful behavior: it produces a versioned, compact packet, includes a semantic hash, and reports savings metrics. However, it does not state whether compilation has side effects, whether it is idempotent, whether it requires existing state, or what canonical truth depends on.

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?

A single dense sentence that packs the purpose, input source, output format, versioning behavior, and computed metrics. There is no filler, and the core action is front-loaded.

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 output schema helps with return values, but the tool still lacks usage guidance and completely omits parameter semantics. For a compile operation with 2 parameters and no annotations, an agent cannot confidently invoke it correctly from this description alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description does not mention family_id or slice_id at all. The description entirely fails to explain what family_id identifies or how slice_id changes compilation, leaving an agent with two parameters and no semantic guidance.

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 states a specific action (compile), a clear source resource (canonical MangoMe truth), and a concrete output (versioned compact UAI/1 execution packet with semantic hash and savings metrics). It is distinct enough from sibling tools like expand_uai_context, decode_uai_result, and compile_execution_context, though it never names them directly.

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?

The description gives no guidance on when to use this tool versus alternatives such as compile_execution_context, expand_uai_context, or read_context. There are no prerequisites, exclusions, or context cues that would help an agent decide this is the right compilation step.

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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