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

With no annotations, the description carries the full disclosure burden and does add real behavioral context: a calibrated Noul-per-candidate path gated by HIPOCAMPO_TYPESAFE=1 with a 0.7 threshold, and a negation-probe embedding fallback with its comparison logic. It does not state whether the operation mutates state or what permissions/cost it incurs, but the disclosed internals are non-obvious and genuinely useful.

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 purpose is correctly front-loaded in one sentence, but the remaining text dumps implementation detail about negation-probe embeddings and threshold machinery that an agent does not need in order to select or call the tool. It is over-specified in the wrong place.

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?

An output schema exists so return values need no explanation, and the single parameter's meaning is partly covered. What is missing is operational context: whether this is a read-only detection pass, whether it is expensive (LLM call per candidate), and when to prefer it over related hippocampus maintenance tools.

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 coverage is 0%, and the sole parameter is documented only as 'ID numérico de la memoria en memoria_vectorial', which clarifies the ID's origin and type beyond the bare schema. That is useful but minimal compensation for a completely undocumented schema, so a baseline-plus score 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?

The opening sentence states a specific verb and resource: 'Detecta contradicciones semánticas de una memoria existente.' The operation is conceptually distinct from siblings like hipocampo_dedup or validate_immune_rule, so an agent can identify it. However, it never differentiates itself from those siblings explicitly, which keeps it short of a 5.

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?

There is no guidance on when to invoke this tool versus alternatives, no prerequisites, and no exclusions. The two execution modes (TypeSafe vs fallback) are described, but those are internal implementation branches, not usage conditions for the agent.

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