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finance_story_discovery

Destructive

Discover key financial narratives and insights from your data. Submit a free-text objective and optional structured inputs to surface trends, anomalies, and storylines.

Instructions

Run the finance domain agent action finance_story_discovery.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior3/5

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

Annotations already mark the tool as non-read-only and destructive, and the description adds useful context that execution is scoped through the dispatcher under JWT, tenant, and company scope. It does not qualify the destructive behavior, but the annotations cover the core safety signal, so this is adequate.

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 short, front-loaded with the action, and uses an Args list for param definitions. The routing sentence earns its place by explaining execution context. Minimal wasted text.

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?

For an agent to invoke this correctly, it still lacks the core functional semantics of finance_story_discovery and selection criteria among dozens of finance and dispatch siblings. Having an output schema covers return values, but does not compensate for the missing 'what does this do and when' information.

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

Parameters3/5

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

The Args block adds basic meaning absent from the schema: message is a free-text objective and inputs is an optional JSON string. However, at 0% schema description coverage, the description should compensate more concretely, and it offers no examples or guidance on valid structured input.

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

Purpose2/5

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

The description opens with 'Run the finance domain agent action finance_story_discovery', which essentially restates the tool name without saying what 'story discovery' produces or means. The routing and scope details explain how execution happens, not what the action accomplishes, so an agent still cannot tell whether this tool fits a finance task.

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?

There is no guidance on when to call this tool versus any alternative such as finance_query_data, finance_chat, or dispatch_domain_agent. The only implication is the action name itself, which is too thin to support confident selection among the large sibling set.

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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