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recommend_learning_path

Create a customized learning plan by analyzing student's subject, current level, learning style, goals, and available study time.

Instructions

Recommend a personalized learning path based on student profile.

Args:
    subject: Subject area
    current_level: Current proficiency: beginner, intermediate, advanced
    learning_style: Learning style: visual, auditory, kinesthetic, reading_writing
    goals: Specific learning goals
    available_hours_per_week: Hours available for study per week

Behavior:
    This tool is read-only and stateless — it produces analysis output
    without modifying any external systems, databases, or files.
    Safe to call repeatedly with identical inputs (idempotent).
    Free tier: 10/day rate limit. Pro tier: unlimited.
    No authentication required for basic usage.

When to use:
    Use this tool when you need structured analysis or classification
    of inputs against established frameworks or standards.

When NOT to use:
    Not suitable for real-time production decision-making without
    human review of results.
Behavioral Transparency:
    - Side Effects: This tool is read-only and produces no side effects. It does not modify
      any external state, databases, or files. All output is computed in-memory and returned
      directly to the caller.
    - Authentication: No authentication required for basic usage. Pro/Enterprise tiers
      require a valid MEOK API key passed via the MEOK_API_KEY environment variable.
    - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are
      included in responses (X-RateLimit-Remaining, X-RateLimit-Reset).
    - Error Handling: Returns structured error objects with 'error' key on failure.
      Never raises unhandled exceptions. Invalid inputs return descriptive validation errors.
    - Idempotency: Fully idempotent — calling with the same inputs always produces the
      same output. Safe to retry on timeout or transient failure.
    - Data Privacy: No input data is stored, logged, or transmitted to external services.
      All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
subjectYes
current_levelNointermediate
learning_styleNovisual
goalsNo
available_hours_per_weekNo
api_keyNo
Behavior5/5

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

Even without annotations, the description thoroughly discloses behavior: read-only, stateless, idempotent, no side effects, authentication requirements, rate limits (free/pro tiers), error handling, and data privacy. This exceeds typical expectations.

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

Conciseness3/5

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

The description is well-structured with sections, but contains redundancy: 'Behavioral Transparency' details appear twice (once in the main description and again after 'When NOT to use'). This could be condensed without losing information.

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?

The description covers many aspects (behavior, rate limits, error handling) but does not describe the format or structure of the successful output (e.g., what a learning path recommendation looks like). Given no output schema, this gap reduces completeness.

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

Parameters5/5

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

The description includes an 'Args' section that describes each parameter, adding meaning beyond the input schema's type/title. For example, 'current_level: Current proficiency: beginner, intermediate, advanced' provides values. With 0% schema description coverage, this fully compensates.

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 clearly states the tool's purpose: 'Recommend a personalized learning path based on student profile.' This is specific and distinct from sibling tools (e.g., analyze_student_progress, create_quiz), which focus on different tasks.

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

Usage Guidelines4/5

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

The description includes explicit 'When to use' and 'When NOT to use' sections, advising to use for structured analysis and cautioning against real-time production use without human review. However, it does not explicitly contrast with sibling tools, but still provides clear guidance.

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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