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GlacianNex

stockdata-mcp

by GlacianNex

fmp_insider_trading

Get insider transaction details for a symbol, or view aggregate buy/sell statistics to assess corporate sentiment.

Instructions

Insider transactions for a symbol, or aggregate insider buy/sell statistics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
symbolYes
statisticsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the tool has two behavioral modes (transactions vs. statistics) but omits critical details such as whether the operation is read-only, output format specifics, pagination (beyond the 'limit' parameter), rate limits, or authentication requirements. Significant gaps remain for a data-retrieval tool.

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 a single, efficient sentence that conveys the core purpose without fluff. However, it is perhaps too terse, missing valuable details that would not add excessive length. It is front-loaded and easy to parse, scoring high on efficiency.

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

Completeness2/5

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

Given the tool has an output schema, the description need not explain return values, but it still lacks essential context about the two modes, the meaning of 'limit', and typical use cases. The description is too sparse to fully guide an agent in selecting and invoking the tool correctly, especially with no annotation support and low schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must explain all parameters. It implicitly suggests that 'symbol' identifies the company and 'statistics' toggles aggregate stats, but it does not explain 'limit' at all. It also fails to clarify the exact meaning of each mode or the expected data structure. The description adds minimal value beyond the parameter names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves insider transactions for a symbol or aggregate buy/sell statistics. It uses the specific verb 'insider transactions' and identifies the resource (symbol) and the two modes. While it's not exhaustive, it distinguishes this from sibling financial data tools like dividends or earnings.

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

Usage Guidelines2/5

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

The description mentions two usage modes ('for a symbol' vs 'aggregate insider buy/sell statistics') but provides no guidance on when to choose this tool over alternatives, nor any exclusions or prerequisites. It does not explain when 'statistics' is appropriate or how it differs from other financial data endpoints.

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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