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saichintamani

sai-roadmap-mcp

Get Learning Roadmap

get_roadmap

Retrieve Sai Chintamani's 2026 AI engineering learning roadmap. Filter by quarter for specific topics.

Instructions

Returns Sai Chintamani's 2026 AI engineering learning roadmap. Optionally filter to a specific quarter (Q1, Q2, Q3, or Q4).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quarterNoOptional quarter to filter the roadmap to
Behavior3/5

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

No annotations, so description carries full burden. Describes read operation but lacks details on side effects, data freshness, or completeness. Adequate but not rich.

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 concise sentences with front-loaded purpose. No wasted words or redundancy.

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?

Simple tool with one optional param, no output schema. Description covers what's returned and filtering, but could mention return structure for full completeness.

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?

Schema coverage is 100% with description of quarter parameter. Description adds value by listing allowed values (Q1-Q4) and clarifying they are quarters of the year.

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?

Clearly specifies verb 'Returns', resource 'Sai Chintamani's 2026 AI engineering learning roadmap', and optional filtering by quarter. Distinguishes from sibling tools like get_certifications, get_profile, get_projects.

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?

Implied usage from context but no explicit guidance on when to use vs alternatives or when not to use. Lacks exclusion criteria.

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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