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Get flag logic (unreduced)

hypertune_get_logic
Read-only

Fetch the underlying LOGIC of flags without reducing them — i.e. query { root { <selection> } } with no context. Returns the flag's conditional expression / rules rather than a single resolved value, useful for inspecting how a flag is configured. If the schema requires a context arg you can still pass a partial one via context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional partial context, inlined as the `context` arg if the schema requires it.
selectionYesGraphQL selection of flag fields under root, e.g. `exampleFlag`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds valuable behavioral detail beyond the schema: it does not reduce flags, it returns configuration logic, and it may accept a partial context when the schema demands one. No contradiction with annotations.

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?

Three sentences with no filler. The core behavior is front-loaded, followed by a concrete query example and a practical edge-case note about partial contexts. Every sentence earns its place.

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?

For a read-only GraphQL query tool with no output schema, the description explains what is returned conceptually (conditional expression / rules), the query shape, and context handling. It does not detail exact response formatting, but that is less critical given the GraphQL nature and no output schema.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds meaning by placing both parameters in the GraphQL query shape, clarifying that 'selection' is the flag field under root and that 'context' is an optional partial inlined when required. This goes beyond the schema's own descriptions.

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 states a specific verb and resource: 'Fetch the underlying LOGIC of flags without reducing them.' It explicitly contrasts with a single resolved value, which distinguishes it from evaluate-like tools even without naming them. The GraphQL query shape is provided, making the tool's function unambiguous.

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 gives clear context: use this to inspect how a flag is configured, especially when you want conditional rules rather than a resolved value. It does not explicitly name sibling tools or state when not to use them, but the contrast with resolved values and the focus on logic provides adequate 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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