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

With no annotations supplied, the description carries the full load and does well: it discloses that this is static text-pattern analysis that does NOT execute the code, that authentication is required, and what class of risk it targets. It stops short of describing the response shape (score vs. finding list), severity semantics, or any limits on code size, which leaves real gaps for a no-annotation tool.

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?

Front-loaded with the core purpose in the first clause, then adds risk rationale, then operational constraints. It is a single dense paragraph and the research citation (October 2026, six named frameworks) is context rather than instruction, but nothing is misleading and the ordering is sensible.

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 tool with no annotations and no output schema, the description covers purpose, static-analysis behavior, and auth, but never tells the agent what comes back (risk verdict, matched patterns, severity) or how to interpret it. That missing return-value framing is the main completeness gap given the absence of 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?

Schema description coverage is 100%, so both parameters are already documented in the schema. The description reinforces what `codigo` should contain but adds no format or size guidance, and it never mentions `lenguaje` (which the schema itself marks as informational and non-behavioral). Baseline 3 applies since the schema does the heavy lifting.

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?

States a specific verb and target: static analysis of AGENT-side orchestration code looking for tool-call extraction from free-text model output (TOOL_CALL:, ```json blocks, <tool_call> tags) instead of the structured tool_calls/function_call/tool_use field. It even names the attack class (Repeat-After-Me) and positions itself against siblings by saying it uses the same approach as detect_sampling_hijack_risk and detect_toxic_flow_risk, so an agent can tell what this tool is and is not.

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?

Clear context for use: point it at the layer that interprets the model response, and it flags parsing of free-text tool calls. It also states the prerequisite (a valid access key, free uses or credits, see POST /crear-llave). It does not explicitly state when to prefer a different detector (e.g. injection vs. hijack vs. spoofing) beyond grouping itself with the other detect_* pattern scanners, so exclusions are implied rather than spelled out.

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