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get_prompt

Get a prompt by name with optional arguments.

Returns the rendered prompt as JSON with a messages array. Arguments should be provided as a dict mapping argument names to values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe name of the prompt to get
argumentsNoOptional arguments for the prompt

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the burden of disclosing behavior. It does mention the return format ('Returns the rendered prompt as JSON with a messages array') and how arguments should be passed, offering some transparency. However, it does not explicitly state that the operation is read-only, what happens if the prompt does not exist, or any permission requirements. The information given is useful but incomplete for full behavioral transparency.

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 consists of three short, front-loaded sentences. The first sentence immediately states the core action and resource, the second clarifies the output structure, and the third clarifies argument formatting. Every sentence contributes meaningful information without any redundant or filler content.

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?

Given the tool's simplicity (2 parameters, no nested objects), the presence of an output schema, and 100% schema parameter coverage, the description provides sufficient information for an agent to select and invoke the tool. It covers the input (prompt name and optional arguments) and output (JSON with messages array). It does not address error cases like missing prompts, but this is a minor gap for such a straightforward getter tool.

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

Parameters3/5

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

The input schema already provides complete descriptions for both parameters (name and arguments), achieving 100% schema description coverage. The description adds a marginal clarification that arguments must be a dict mapping names to values, but this is already implied by the schema's object type with additionalProperties. Thus, the description adds limited value beyond the schema, warranting the baseline score of 3.

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 function: 'Get a prompt by name with optional arguments.' This uses a specific verb and resource, and distinguishes it from siblings like get_doc or get_section by referencing 'prompt.' It also specifies the output format ('rendered prompt as JSON with a messages array'), leaving no ambiguity about what the tool does.

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 description implies usage when you have a prompt name and want the rendered output, but it does not provide explicit guidance on when to use this tool versus alternatives like list_prompts or get_section. There are no exclusions or direct comparisons, so the usage context remains implied rather than clearly specified.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: get_doc reads full files, get_section reads specific sections, list_docs and list_sections provide navigation, search_docs and resolve_topic offer different search methods, get_functions and validate_function handle function lookup, and get_prompt/list_prompts cover prompts. No two tools overlap in functionality.

Naming Consistency5/5

All tool names follow the verb_noun pattern consistently (e.g., get_doc, list_sections, search_docs). The naming convention is uniform with lowercase and underscores, making it predictable and easy for an agent to infer behavior.

Tool Count5/5

With 10 tools, the count is well-scoped for a documentation and function lookup server. It provides sufficient coverage without being overwhelming, fitting within the ideal range of 3-15 tools.

Completeness5/5

The tool surface comprehensively covers documentation discovery, reading, searching, navigation, and function validation. There are no obvious gaps for the stated purpose of accessing Pine Script v6 documentation and functions.

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