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export_context_markdown

Export project context to a Markdown file for sharing with LLMs and AI tools. Provide the project root directory to generate the document.

Instructions

Export the project context as a Markdown document for sharing with other LLMs and AI tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoProject root directory..

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It does not state whether the operation is read-only, whether it creates a file or returns content, or what exactly is included in 'project context'. The word 'export' suggests non-destructive behavior, but the lack of explicit side-effect or permission information is a significant gap.

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 a single, concise sentence that front-loads the action and purpose. It contains no redundant or filler information, earning the highest score for conciseness.

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?

This is a simple tool with one parameter, a full schema, and an output schema, so the description doesn't need to explain return values. The core behavior is clearly stated. However, the meaning of 'project context' is somewhat ambiguous (e.g., does it include all context, decisions, tasks?), but given the simplicity and output schema, the description is adequate.

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 describes the only parameter 'path' with a default and clear description ('Project root directory.'). Schema coverage is 100%, so the description adds no extra parameter semantics. Baseline of 3 applies because the schema carries the full burden.

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 uses a specific verb 'Export' with a clear resource 'project context' and output format 'Markdown document', and it states the intended use case (sharing with other LLMs). This clearly distinguishes its core function, but does not explicitly differentiate from sibling tools like generate_handoff or generate_project_brain, which could also produce context-related documents.

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 one wants to share project context with other LLMs/AI tools. However, it gives no explicit guidance on when to use this tool instead of alternatives (e.g., generate_handoff, get_context) or any exclusions. The use case is stated but not contrasted with sibling 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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