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scan_pledge_risks

Scan multiple NSE stocks for promoter pledge risks, sorted by critical level, to quickly identify dangerous holdings in your watchlist.

Instructions

Scan multiple NSE stocks for promoter pledge risk simultaneously.

Returns results sorted by risk level (critical first). Useful for screening your watchlist or Nifty 500 for pledge dangers.

Args: symbols: list of NSE symbols (e.g. ["ADANIENT", "ZEEL", "RELIANCE", "TCS"])

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description carries full burden. It discloses that the tool scans multiple stocks simultaneously and returns sorted results, implying a read-only operation. This is sufficient, though it could mention that no data is modified or provide more detail on risk criteria.

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?

The description is concise with three sentences plus an args section, all front-loaded with key information. Every sentence adds value: purpose, behavior, usage, and parameter details. No waste.

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

Completeness5/5

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

Given the existence of an output schema (not shown), the description need not detail return values. It covers what the tool does, how to use it, and an example parameter. For a simple scan tool, this is complete and sufficient for an agent to invoke it correctly.

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 0%, so the description must compensate. It provides an example and clarifies that symbols are NSE symbols (e.g., 'ADANIENT'), adding meaning beyond the schema's type-only definition. This helps the agent understand parameter format.

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?

The description clearly states the tool scans multiple NSE stocks for promoter pledge risk simultaneously, which distinguishes it from sibling tools like 'promoter_pledge' that may handle single stocks. The verb 'scan' and resource 'promoter pledge risk' are specific, and sorting by risk level is mentioned.

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

Usage Guidelines4/5

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

Provides a clear use case: 'useful for screening your watchlist or Nifty 500 for pledge dangers.' However, it does not explicitly state when not to use this tool or mention alternatives, such as single-stock pledge tools, leaving some ambiguity for the agent.

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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