Run all five analyses in one call: language detection, natural-language explanation, docstring generation, complexity metrics, and refactoring suggestions.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The code snippet to analyze | |
| language | No | Programming language (optional, auto-detected if omitted) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states that all five analyses are run, but does not disclose what the combined output looks like, whether it returns a single object or multiple, or any performance implications. It lacks detail about the response format and potential partial-failure behavior.
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 that front-loads the main purpose, then lists the five analyses. Every word earns its place; no redundancy or filler.
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?
The tool is an aggregation of five analyses, which is moderately complex, and there is no output schema. The description explains what the tool runs but does not describe the shape of the response or how the combined results are organized. It is complete enough for basic usage but lacks expected return-value details.
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 covers both parameters (code and language) with descriptions, so the baseline is 3. The description does not add any additional meaning to the parameters, but given 100% schema coverage, no compensation is needed.
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 the tool runs all five analyses in one call and explicitly lists them, using a specific verb ('Run') and resource ('all five analyses'). It distinguishes itself from the sibling tools, which handle individual analyses.
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 implies when to use this tool: when you want all five analyses at once. However, it does not explicitly contrast with the individual sibling tools or state when not to use it (e.g., 'for a single analysis, use the specific tool instead').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of code analysis: language detection, explanation, docstring generation, complexity metrics, and refactoring suggestions. analyze_all is explicitly a combined wrapper, so agents won't confuse it with individual tools.
All tool names follow a consistent verb_noun pattern (e.g., detect_language, explain_code, generate_docstring). analyze_all uses the same verb-first structure, with 'all' as the object, preserving the convention.
Six tools is an ideal size for a code analysis server, covering the main analysis categories without bloat. Each tool provides a distinct value and the combined analyze_all tool adds convenience without unnecessary overhead.
The tool surface comprehensively covers the domain of code explanation and analysis: language detection, natural-language explanation, docstring generation, complexity assessment, and refactoring suggestions. The analyze_all tool ensures all features are accessible in one call, leaving no obvious gaps for common code-explanation workflows.