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Generate coding prompt

generate_prompt
Read-only

Convert an annotation into a ready-to-paste coding prompt formatted for your target AI assistant (Claude, Copilot, Cursor, etc.) using a deterministic template with no AI spend.

Instructions

Render a ready-to-paste coding prompt for an annotation, formatted for a target assistant. A deterministic template (no AI spend); for a deeper analysis use diagnose_annotation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNoWhich assistant to format for. Defaults to generic.
annotation_idYesThe id of the annotation to turn into a prompt.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptNo
targetNo
Behavior4/5

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

The description goes beyond the readOnlyHint by disclosing a deterministic template and 'no AI spend,' which are useful behavioral traits not captured by the annotations. It doesn't contradict annotations. While it doesn't detail return format, the output schema covers that, so this is adequate.

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 two sentences long and front-loaded with the main purpose. Every word earns its place: the first sentence defines the action, the second adds a key behavioral note and an alternative. No fillers or repetition.

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?

With a simple tool (2 parameters, 1 required), full schema descriptions, an output schema, and readOnly/destructive annotations, the description is complete. It gives the essential behavioral context (deterministic, no AI spend) and points to a sibling for deeper needs, leaving no significant gaps.

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 full descriptions for both parameters (annotation_id and target), covering 100% of the schema. The description does not add extra meaning to the parameters beyond what the schema states, so a baseline score of 3 is appropriate.

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 uses a specific verb 'Render' and clearly identifies the resource: 'a ready-to-paste coding prompt for an annotation, formatted for a target assistant.' It also distinguishes itself from siblings by explicitly noting it is a deterministic template and pointing to diagnose_annotation for deeper analysis.

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

Usage Guidelines5/5

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

The description states when to use this tool: to generate a deterministic, no-AI-spend prompt with a specific output format. It explicitly names an alternative for deeper analysis ('for a deeper analysis use diagnose_annotation'), providing clear guidance on choosing between tools.

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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