skills
Rahul's skills, grouped by category (Languages, Frontend, Backend, AI & Agents, Cloud & Infra).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Rahul's skills, grouped by category (Languages, Frontend, Backend, AI & Agents, Cloud & Infra).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| 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?
No annotations are provided, so the description carries the burden. It discloses the grouping behavior and category names, which is useful. However, it doesn't state whether the output is a static list, whether it includes proficiency levels, or whether it's read-only. The lack of annotations makes this a moderate gap, but the description does add meaningful behavioral context beyond the empty schema.
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?
A single sentence that is front-loaded with the resource name and immediately provides the grouping structure. No wasted words.
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?
For a zero-parameter, read-only-looking tool with an output schema, the description is largely complete. It could mention that this is a static profile section or that it returns a categorized list, but the grouping and categories are already stated. The output schema likely covers the return structure, so nothing critical is missing.
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 zero parameters, so there is no parameter semantics burden. The description adds value by explaining the grouping and categories, which is the only meaningful semantic content. Baseline 4 for zero params 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 a clear resource ('Rahul's skills') and a specific organizing principle ('grouped by category'), listing the categories. It distinguishes itself from siblings like education and experience by naming the resource and grouping. It doesn't use a verb like 'list' or 'show', but the intent is unambiguous.
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 implies this tool is for retrieving skills data, and the sibling names (education, experience, projects) suggest alternatives for other resume sections. However, it doesn't explicitly state when to use this tool versus a sibling, nor does it mention any context like 'use for skill-related queries'.
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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