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rodhayl
by rodhayl

generate_agents_md

Generate AGENTS.md documentation from project structure. Use LLM to enhance with README insights or disable for faster static output.

Instructions

Generate AGENTS.md from project structure. useLlm=false for faster static output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootNoProject root directory (default: workspace root)
outputPathNoOutput file path relative to root (default: .mcp-local-llm/AGENTS.md)
overwriteNoWhether to overwrite existing file (default: false)
useLlmNoUse LLM to enhance content with README insights (default: true). Set false for fast static generation.
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It hints at the speed/quality trade-off via the useLlm parameter, but fails to disclose file system mutation behavior (overwriting, creating directories), idempotency, or what happens when the file already exists (though the 'overwrite' parameter implies this scenario).

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 exactly two sentences with zero waste. The first sentence front-loads the core purpose (generating AGENTS.md), while the second provides a targeted usage tip for the useLlm parameter. Every word earns its place.

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

Completeness3/5

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

Given 100% schema coverage and 4 optional parameters, the description adequately covers the basic invocation pattern. However, lacking an output schema and any description of return values or error conditions (e.g., what happens if the directory doesn't exist), it remains minimally viable rather than comprehensive for a file-generation tool.

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

Parameters4/5

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

With 100% schema coverage, the baseline is 3. The description adds valuable semantic context for the useLlm parameter by clarifying that false means 'faster static output' versus the schema's generic 'enhance content' description, effectively guiding the performance/quality trade-off decision.

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 specific action (Generate), the target resource (AGENTS.md), and the source data (project structure). However, it does not distinguish from the sibling tool 'generate_docs' or explain what AGENTS.md represents, leaving ambiguity about why an agent would choose this over other documentation generators.

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 provides implied usage guidance for the useLlm parameter ('useLlm=false for faster static output'), suggesting when to disable LLM enhancement for speed. However, it lacks explicit guidance on when to use this tool versus siblings like 'generate_docs' or prerequisites like requiring a project structure to analyze.

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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