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generate_cursor_guidance

Creates advisory guidance snippets for Cursor to recommend suitable LLM models without forced selection.

Instructions

Generate advisory Cursor guidance snippets. Does not apply or enforce model selection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configNo
planPathYes
repoPathNo
Behavior2/5

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

No annotations exist; description adds minimal behavioral context (advisory, non-enforcing) but omits side effects, auth needs, or rate limits.

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?

Two sentences, front-loaded with key info, no filler – every word earns its place.

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

Completeness1/5

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

With no output schema, no annotations, and no parameter descriptions, the description alone is woefully inadequate for safe and correct tool use.

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 coverage is 0% and description mentions no parameters; schema properties (config, planPath, repoPath) have no explanations, leaving agent guessing.

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?

Description clearly states the tool generates advisory Cursor guidance snippets and explicitly distinguishes from enforcing model selection, making purpose distinct from sibling tools.

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?

No guidance on when to use this tool versus alternatives; no prerequisites, exclusions (beyond one line), or context cues provided.

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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