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get_prompt_template

Retrieve the canonical English prompt template for Ambari operations. Optionally fetch a specific section or list all headings.

Instructions

Return the canonical English prompt template (optionally a specific section).

Simplified per project decision: only a single English template file PROMPT_TEMPLATE.md is maintained.

Args: section: (optional) section number or keyword (case-insensitive) e.g. "1", "purpose", "tool map". mode: (optional) if "headings" returns just the list of section headings with numeric indices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionNo
modeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It explains that the tool returns the full template or a specific section, and a headings mode. It does not mention permissions, error handling, or other behavioral traits, but for a simple read operation, the description is sufficiently transparent.

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 concise, with the main purpose in the first sentence, followed by a brief note on project decision and parameter details. Every sentence adds value, with no unnecessary words.

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

Completeness5/5

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

Given the existence of an output schema, the description does not need to explain return values. It covers the parameters thoroughly, and the tool's complexity is low (2 optional params). The description is complete for an agent to understand and invoke the tool correctly.

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

Parameters5/5

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. It does so by explaining both parameters: 'section' (optional section number or keyword) and 'mode' (if 'headings' returns heading list). This adds meaningful context beyond the schema's basic type definitions.

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's purpose: 'Return the canonical English prompt template (optionally a specific section).' The verb 'Return' and resource 'prompt template' are specific, and the tool is distinct from siblings which deal with different domains like cluster management or metrics.

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 explains the project decision (only one file) and the optional parameters, providing context for usage. However, it does not explicitly state when to use this tool over alternatives or when not to use it. Since it is the sole tool for this purpose, the guidance is adequate but lacks explicit exclusion or alternatives.

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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