promoter_pledge

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

With no annotations provided, the description carries the full burden. It describes return content and the risk signal logic, and examples clarify expected behavior. However, it does not explicitly state that this is a read-only query, nor does it disclose potential error behaviors (e.g., invalid symbol handling) or data availability limits. The description is transparent about what data comes back but could be more explicit about operational behavior.

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 well-structured and front-loaded with the primary purpose. It uses bullet points for provided data, a clear Args section, and examples. Every sentence earns its place, covering rationale, risk interpretation, and usage without being verbose.

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?

For a single-parameter tool with an output schema, the description is nearly complete. It explains why the data matters, what the risk signal means, and what outputs to expect. The only gaps are edge cases like unavailable data or invalid symbols, but these are minor for a simple lookup tool.

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 schema has one parameter 'symbol' with zero description coverage. The description compensates fully by defining it as 'NSE stock symbol (e.g., RELIANCE, TCS, ADANIENT)' and providing two usage examples. This adds meaningful context beyond the raw schema and demonstrates correct invocation.

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 tool's purpose: 'Promoter pledge percentage — how much of promoter holding is pledged as loan collateral.' This is a specific verb+resource combination. It also lists exact outputs (promoter pledge % of total shares, pledge % of promoter holding, risk signal, quarter-wise breakdown) and distinguishes from sibling tools like promoter_shareholding by focusing specifically on pledge data.

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 implies when to use this tool (when checking pledge risk for a stock) and adds context about NSE publishing the data free vs Screener.in Pro. However, it does not explicitly compare to alternatives like get_pledge_alert or scan_pledge_risks, nor does it state exclusions for when not to use it. Usage guidance is present but implicit.

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