InsightSentry MCP

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

With no annotations provided, the description carries full behavioral disclosure burden. It details the complex return structure (code, data array with hundreds of fields, last_update timestamp) and explains the filtering mechanism to reduce token usage. Lacks explicit mention of rate limits or caching, but comprehensively describes the payload structure and filtering capabilities.

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

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

Information-dense but well-structured with clear progression: summary → return format → data volume warning → filter examples → prerequisite tools → sibling alternatives. Every sentence provides actionable guidance. Slightly dense but justified by the tool's complexity.

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

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

Given the tool returns hundreds of fields with no structured output schema available, the description adequately compensates by documenting the return structure inline. It covers the discovery workflow (get_fundamentals_meta prerequisite), filtering strategies, and appropriate presentation patterns. Could mention pagination or rate limiting, but substantially complete for the complexity level.

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

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

While the schema has 100% coverage (baseline 3), the description adds concrete JSONata syntax examples for the filter parameter: 'data[category='Valuation']' and '$distinct(data.category)'. These practical examples significantly enhance understanding of how to use the optional filter parameter effectively.

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

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

The description clearly states it retrieves 'comprehensive fundamental data' and lists specific categories (valuation ratios, profitability metrics, balance sheet, etc.). It explicitly distinguishes from siblings by directing users to get_fundamentals_series for historical data and get_fundamentals_meta for field discovery.

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

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

Provides explicit when-to-use guidance: 'For historical fundamentals use get_fundamentals_series' and 'If you're unsure which fields exist, call get_fundamentals_meta first.' Also includes prescriptive guidance on presentation: 'Present only the fields relevant to the user's question — do NOT dump the entire response.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.