Zerodha MCP Integration

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action ('Cancel') but doesn't disclose critical traits like whether cancellation is reversible, requires specific permissions, has side effects (e.g., on account status), or returns confirmation details. This is inadequate for a mutation tool with zero annotation coverage.

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?

The description is appropriately sized and front-loaded, with the core purpose in the first line and parameter details following. It avoids unnecessary elaboration, though the 'Args' formatting could be more integrated with the main text for better flow.

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's complexity (a destructive mutation with no annotations, 0% schema coverage, and no output schema), the description is insufficient. It lacks details on behavior, error conditions, return values, and integration with sibling tools, leaving significant gaps for an AI agent to operate effectively.

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?

The description includes an 'Args' section that documents the single parameter 'order_id', adding meaning beyond the schema (which has 0% description coverage). However, it only states 'Order ID to cancel' without explaining format, source (e.g., from 'get_mf_orders'), or validation rules, providing basic but incomplete semantic context.

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 the verb ('Cancel') and resource ('a mutual fund order'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'cancel_mf_sip' or explain what distinguishes a mutual fund order from other order types, which prevents a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the order must be in a cancellable state), exclusions, or relationships with sibling tools like 'place_mf_order' or 'get_mf_orders', leaving usage context unclear.

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