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generate_llm_context

Generate a detailed LLM context file documenting all tools, memory system, and workflows for easy @-reference.

Instructions

Generate a comprehensive LLM context reference file documenting all tools, memory system, and workflows for easy @ reference

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathYesPath to the project root directory where LLM_CONTEXT.md will be generated
includeExamplesNoInclude usage examples for tools
formatNoLevel of detail in the generated contextdetailed
Behavior2/5

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

No annotations are provided, so the description carries full burden. It does not disclose whether the tool overwrites existing files, side effects, permissions needed, or anything about the generated file's location or content. The schema parameter description hints at LLM_CONTEXT.md but the tool description itself is vague.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that conveys the core purpose without unnecessary words. It could be more structured but remains concise.

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

Completeness2/5

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

Given no output schema, the description should explain the output format or content. It only says 'comprehensive LLM context reference file', lacking details on what that includes. This is insufficient for a tool generating a file.

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 has 100% description coverage, so the schema already documents parameters. The tool description adds no extra meaning beyond the schema, meeting the baseline expectation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a comprehensive LLM context reference file documenting all tools, memory system, and workflows. The verb 'generate' and resource are specific, and it distinguishes from sibling tools like generate_config and generate_contextual_content which have different purposes.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or specific scenarios. Given the many sibling tools, this is a significant gap.

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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