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

Annotations already declare readOnly, non-destructive, open-world, so the safety profile is covered. The description adds genuine behavioral context beyond that: the underlying dataset lags live MCA records by a few months, producing legitimate not-found results for new entities. That is exactly the kind of gotcha an agent needs and would otherwise misread as an error.

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?

Three sentences, front-loaded with purpose, then the workflow hand-off, then the caveat. Nothing is redundant and the ordering matches how an agent would read it.

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?

Single-parameter read tool with no output schema, and the description nonetheless enumerates the returned fields and the data-freshness caveat. An agent has everything needed to call it and correctly interpret an empty result.

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?

Schema coverage is 100% and the schema already documents the CIN/LLPIN formats with examples and the 21-character length. The description restates 'CIN or LLPIN' but adds no parsing rules, validation behavior, or normalization hints beyond what the schema supplies, so it lands at the baseline.

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?

States a specific verb (looks up), a specific resource (Indian company or LLP), the authoritative source (MCA data on data.gov.in), and the exact fields returned (name, type, incorporation date, MCA status, RoC). This is clearly distinguishable from every sibling (compliance_calendar, mca_late_fee, msme_interest), which handle different tasks.

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?

Gives concrete downstream routing — 'Feed the type and date into compliance_calendar' — which tells the agent where this tool sits in a workflow. It also flags the key failure mode (recently incorporated companies may not be found). It stops short of naming an alternative tool when a company isn't found, so it isn't a full when/when-not/alternatives statement.

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