Get Exploit AI Analysis

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, indicating a safe, non-destructive, idempotent read operation. The description adds extensive behavioral context by listing all the analysis fields returned (classification, attack type, complexity, reliability, confidence score, authentication requirements, target software, summary, prerequisites, MITRE ATT&CK techniques, deception indicators, backdoor-review verdict, operator-risk notes). This goes well beyond annotations to inform the agent about what the tool reveals.

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 concise (3 sentences) and front-loaded: first sentence states purpose, second details return fields, third gives usage guidance and an example. Every sentence is informative and earns its place. No redundant or vague language.

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 (returns many analysis fields) and absence of output schema, the description is remarkably complete. It enumerates all major return components (classification, attack type, complexity, reliability, confidence score, authentication, target software, summary, prerequisites, MITRE ATT&CK, deception indicators, backdoor-review verdict, operator-risk notes). This fully equips the agent to understand what the tool returns without needing an output schema.

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 input schema describes the parameter 'exploit_id' with description 'Platform exploit ID (the [id=XXXXX] number from results — NOT the EDB number).' The description adds meaning by clarifying it is the platform exploit ID, not the EDB number, and referencing the result format. With 100% schema coverage and a single parameter, this extra clarification ensures the agent correctly identifies which ID to use.

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's purpose: 'Get the full AI analysis for a single exploit by its platform ID.' It lists the specific analysis components returned (classification, attack type, etc.), distinguishing it from sibling tools like get_exploit_code (which gets code) or get_author (author info). The verb 'Get' and resource 'AI analysis' are specific and unique among siblings.

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 provides a clear use case: 'Use this to check if an exploit is safe before reviewing its code.' This tells the agent when to invoke the tool. It also includes an example (exploit_id=61514) to illustrate. However, it does not explicitly state when not to use it or mention alternative tools for different contexts, slightly lowering the score.

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