stocktoken_metrics
Operational metrics for this AI Agent Tokenized Stock OS process.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Operational metrics for this AI Agent Tokenized Stock OS process.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. However, it only says 'operational metrics' without revealing side effects, permissions, rate limits, or expected output, leaving the tool's behavior largely opaque.
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 a single short sentence, which is concise but not sufficiently informative. It earns its place but could be improved with more detail without becoming 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?
Given the lack of output schema and annotations, the description should provide enough context about what the tool returns or requires. 'Operational metrics' is too vague, and no information about expected output or usage context is given, making it incomplete for an agent to use confidently.
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 tool has no parameters, and the schema coverage is trivially 100%. The description does not add parameter semantics, but none are needed. Baseline 3 is appropriate.
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 states it provides 'operational metrics' but does not specify what kind of metrics or what 'process' it refers to. It gives a general sense but lacks specificity to fully distinguish it from other informational tools like stocktoken_get or stocktoken_list.
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?
No guidance is given on when to use this tool versus its many siblings. There is no mention of appropriate contexts, prerequisites, or alternatives.
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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