deep_scan_content_tool

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

In the absence of annotations, description discloses important behavioral traits: L1 for stats, L2/L3 analyze raw content, and higher risk of Q-Agent compromise. This adds transparency beyond the 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?

Description is concise with only a few sentences, each adding value. Could be slightly more streamlined, but overall efficient.

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 output schema exists, return values are covered externally. Description covers key behavioral aspects but omits error conditions or prerequisites. Adequate for a simple tool.

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 100%, so schema already documents both parameters. The description adds minimal new meaning beyond noting content is 'raw unsanitized', so baseline score 3 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?

Description clearly states it performs a deep security scan on inline content, mentioning L1/L2/L3 levels and distinguishing from scan_content via cross-reference. However, it could more explicitly differentiate from similar sibling tools like quarantine_scan_tool.

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?

Provides context about L1/L2/L3 behavior and advises cross-referencing with scan_content for completeness, but lacks explicit when-to-use or when-not-to-use guidance relative to alternatives.

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