atlas_explain

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It lists the types of analysis provided but does not explicitly state that the tool is read-only, what the return format looks like, or any limitations (e.g., handling malformed code). The read-only nature is implied by the word 'explain' but not explicitly disclosed.

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, focused sentence. It front-loads the primary purpose ('Explain code in plain language') and then lists key features without unnecessary words. It is concise and well-structured.

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's complexity (7 parameters, no output schema, no annotations), the description does a good job of establishing purpose and core capabilities. However, it lacks explicit details on return value format and how parameters interact (e.g., whether 'includePatterns' is ignored when type is 'line-by-line'). This leaves some gaps for an AI agent, but it is still usable for typical scenarios.

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 descriptions cover all 7 parameters (100% coverage), so the baseline is 3. The description adds value beyond the schema by naming specific explanation modes (line-by-line, algorithm analysis, complexity, design patterns) that map to the 'type', 'includePatterns', and 'includeComplexity' parameters, helping the agent choose appropriate values. It also hints at the 'level' parameter with 'beginner-friendly glossary'.

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 action ('Explain code in plain language') and specifies the resource (code). It enumerates distinct capabilities (line-by-line explanations, algorithm analysis, complexity analysis, design pattern detection, glossary) that differentiate it from sibling tools like atlas_docs or atlas_critique.

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 gives clear context for when to use the tool: when code needs to be explained in plain language. It lists typical use cases (line-by-line, complexity, design patterns). However, it does not explicitly mention when not to use it or direct users to alternative tools, such as atlas_docs for documentation generation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.