score_lead
Composite 0-100 lead score combining audit + demand signal.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| niche | No | ||
| business_name | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Composite 0-100 lead score combining audit + demand signal.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| niche | No | ||
| business_name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It mentions combining two signals but omits details on idempotency, side effects, permissions, or error handling. The description does not confirm if the tool is read-only or if it modifies data.
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 sentence, which is concise but lacks structure. It does not front-load critical information or organize details logically. It could be expanded without losing conciseness.
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 three parameters and an output schema, the description is too minimal. It does not explain how the score is computed or what the output represents (despite having an output schema, it is not referenced). The context of 'audit + demand signal' is vague.
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?
Schema description coverage is 0%, yet the description does not explain any of the three parameters (business_name, city, niche). It does not map 'audit' or 'demand signal' to these parameters, leaving their semantics completely unclear.
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 clearly states that the tool computes a composite 0-100 lead score from audit and demand signals. It specifies the range and components, making the purpose understandable. However, it does not use a strong verb like 'calculate' or 'generate', and it does not differentiate from sibling tools.
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 provided on when to use this tool versus alternatives, such as when a lead should be scored or what prerequisites exist. Sibling tools are listed but not explained in relation to this tool.
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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