systems_apply
Apply a saved scoring system to evaluate stocks and automatically increment its usage count.
Instructions
Apply a saved scoring system (increments its usage count).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| system_id | Yes |
Apply a saved scoring system to evaluate stocks and automatically increment its usage count.
Apply a saved scoring system (increments its usage count).
| Name | Required | Description | Default |
|---|---|---|---|
| system_id | Yes |
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already cover readOnlyHint=false, idempotentHint=false, destructiveHint=false, and openWorldHint=true, so the baseline burden on the description is lower. The parenthetical about incrementing usage count adds useful behavioral context about a side effect that is not visible in the schema or annotations. It does not contradict annotations.
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, compact sentence and the most important behavioral distinction (usage count side effect) is included in parentheses without bloating. It earns its place, though it could define 'apply' somewhat more.
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 tool has only one parameter, no output schema, and sibling names largely self-explanatory (systems_* family), the single-sentence description is mostly sufficient for an agent to call it correctly. A minor gap is that it does not say anything about the return value or when applying is valid, but the simplicity of the operation and the annotations keep the definition reasonably complete.
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 schema has only one required integer parameter, system_id, and the schema description coverage is 0% so the schema itself doesn't explain it. The description names the resource ('saved scoring system') which implies system_id refers to the ID of that saved system, adding some meaning. However, it doesn't explicitly state the format/requirements of system_id or explain what 'apply' results in.
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 uses a specific verb 'Apply' plus resource 'saved scoring system' and even clarifies the side-effect ('increments its usage count'). This makes it clearly distinct from sibling tools like systems_show, systems_list, systems_create, systems_update, and systems_delete, which involve other operations on scoring systems.
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?
The description clearly states that this tool applies a saved scoring system, implying it is used when the agent needs to activate or use an existing scoring system. It does not explicitly name alternatives or say 'when NOT to use', but among the systems_* siblings the verb 'apply' is distinct enough to convey the intended usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.