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detect_pump

Detect pump-and-dump operator activity in NSE stocks by analyzing volume spikes, price surges, and circuit patterns. Returns pump probability, red flags, and recommendations.

Instructions

Detect pump-and-dump operator activity in an NSE stock.

Scans for coordinated pump patterns:

  • Volume spike > 3x 20-day average

  • Price surge > 20% in 5 days without news

  • Multiple upper circuit days in last week

  • Micro/small cap (highest vulnerability)

"This microcap hit 3 upper circuits in a week — 9 out of 10 times this reverses violently"

Returns:

  • pump_probability: low / medium / high / critical

  • red_flags: specific signals that fired

  • verdict + recommendation (exit / avoid / cautious)

Args: symbol: NSE symbol (most useful for small/micro caps)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description lists criteria scanned (volume spike, price surge, etc.), expected output (pump_probability, red_flags, verdict+recommendation), and includes a realistic example. This fully compensates for the lack of annotations.

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

Conciseness4/5

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

The description is well-structured with clear sections: purpose, scan criteria, example, returns, and args. It is front-loaded with the key action. However, the inclusion of a quote and example adds some verbosity that could be trimmed for conciseness.

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?

For a single-parameter tool with an output schema (implied by 'Returns'), the description covers input, analysis logic, and output fields thoroughly. No critical gaps remain given the tool's complexity.

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?

With 0% schema description coverage, the description adds value by specifying 'NSE symbol (most useful for small/micro caps)', providing context beyond the schema's bare 'string' type. It could further specify format (e.g., 'RELIANCE') but is adequate.

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 'Detect pump-and-dump operator activity in an NSE stock' which is a specific verb+resource. It uniquely identifies the tool's purpose among many sibling tools, as no other tool explicitly targets pump-and-dump detection.

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?

The description provides guidance on when the tool is most applicable by noting 'most useful for small/micro caps' in the args section. However, it does not explicitly compare to siblings or state when not to use it.

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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