fluig_dataset_history

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

With no annotations, the description carries the full burden and does so unusually well: it discloses that the route ignores fields/expand, that every item is ~8 KB, that pageSize defaults to 3 and source is truncated, and — critically — that history is immutable so secrets (passwords) previously in a dataset stay readable. These are exactly the surprising behaviors an agent must know.

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?

Two warning-prefixed sentences, front-loaded with the core identity and analogy, then the two gotchas. Zero filler; every clause conveys a distinct behavioral constraint.

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?

Covers the critical behavioral traps for a read tool with no annotations and no output schema. Minor gaps remain (auth requirements, exact response shape beyond 'source per version'), but nothing an agent needs to call it correctly is missing.

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 100%, so baseline is 3; the description adds value beyond the schema by explaining the *reason* for pageSize=3 and truncar=true defaults (context cost, ~8 KB per item), which the schema only states as values.

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 resource ('HISTÓRICO de versões de um dataset, com o código-fonte') and nails it with the 'git log' analogy. An agent can immediately distinguish this from fluig_dataset_get (current source), fluig_dataset_list, or fluig_dataset_run without opening a schema.

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?

Implied use is very clear — retrieve a dataset's version history. It also gives operational guidance (pageSize defaults, truncation) that shapes the call. It stops short of explicitly naming alternatives like fluig_dataset_get for the current source, so no explicit when/when-not routing.

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