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

With no annotations, the description carries the full burden. It discloses the checks performed but not the safety profile: whether the tool only reads/validates or actually mutates state, what "block RAG Data Poisoning" means operationally (hard rejection, flagging, or blocking a job), or whether it consumes gas/credits or requires authorization. The pass/fail return shape is also unstated, leaving the agent guessing at how to interpret the result.

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 same content is repeated three times in EN/ES/ZH, tripling length without adding information for any single reader. The core check list is front-loaded and readable in the first sentence, but the multilingual duplication violates the "every sentence earns its place" bar.

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 3-parameter validation tool with no annotations and no output schema, an agent needs parameter structures and result semantics spelled out, and neither is present. The description explains what is validated but not what input to supply, what a success or failure looks like, or what happens to poisoned data after detection.

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 0%, so all meaning must come from prose, and the description supplies almost none: it never mentions the three parameters by name. It gestures at expectedDimension via "vector dimensions" and at chunks via "cloned chunks", but minChunks, the required chunks array element structure, and accepted formats are entirely undocumented.

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 names a specific verb ("Verify") and concrete resources (vector dimensions, L2 norm, cloned chunks) and scopes itself as "Vertical 6 (RAG Knowledge Bases & Vector Embeddings)", which distinguishes it from the hiperspace of other audit_* siblings covering skills, inference, SLA, GPU, backtests, and smart contracts. The purpose is clear without opening the schema, though the odd "escrow" framing in the tool name is never explained.

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?

Usage is only implied by the enumerated checks (dimension consistency, non-zero/NaN L2 norm, no cloned chunks, poisoning prevention) – an agent can infer this is the RAG-embedding audit and not the skill or GPU audit. There is no explicit when-to-use statement, no prerequisites (e.g., must chunks come from a prior escrow job?), and no named alternative for non-vector content.

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