fluig_service_list

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

With no annotations, the description carries the full burden and does well: it discloses a non-obvious side effect (runs through fluig_db_query and writes a dataset), a deliberate safety constraint (fixed projection excludes credential columns), and a production confirmation guard. It stops short of covering auth requirements, cost, or result size/pagination.

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?

Three short sentences, front-loaded with purpose then the two safety notes; every sentence carries distinct information and nothing is repeated.

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?

There is no output schema, and the description compensates by naming the returned columns, plus flags the write-through to a dataset and the prod guard. Only minor gaps remain (pagination/volume, auth) for a two-parameter read-like listing.

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 the schema already documents env (enum with explicit prod/teste semantics) and confirm. The description only restates the prod/confirm rule, adding no syntax or behavior beyond the structured fields — baseline 3 applies.

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 resource (integration services registered in Fluig) and enumerates the exact projected fields (name, URL, type, driver), plus the business value (understanding how the environment talks to RM and third parties). It is clearly distinguishable from dataset/process siblings, though it doesn't name a specific alternative 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?

Gives a clear use context ('útil para descobrir como o ambiente fala com o RM e com terceiros') and a hard precondition (confirm=true in prod). It does not, however, state when NOT to use it or point to a sibling for a related need.

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