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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description goes well beyond: internal notes are never counted or shown, pagination via cursor/next_cursor, visibility rules ('every member of the token's company sees and can answer every case'), reply delivery (thread + email followers), a text-only limitation, and that agent writes are labelled 'via AI agent'.

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 purpose and the pre-check heuristic before the denser reference material (item fields, status glossary). Dense and every paragraph is useful, but it is long and the title sentence is repeated verbatim at the top, adding minor redundancy.

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?

No output schema, yet the description enumerates returned fields and their meaning (id vs number, status values with lifecycle notes), describes filtering defaults, pagination, and visibility/write-side behavior. Nothing needed 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?

With 25% schema coverage the description carries most of the load and does so well: scope=mine meaning, state=open/closed semantics and defaults, and cursor/next_cursor paging are all explained beyond the raw schema. The one gap is `limit`, whose default and ceiling are left to the schema, so it falls short of fully compensating.

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+resource (support cases) with scope qualifiers (company-wide, any member, newest activity first) and immediately distinguishes the domain from issues via 'Support cases = asking the BoardMark team for help.' An agent can tell this apart from get_support_case and search_issues 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?

Explicit when-to-use ('when the user wants help from the BoardMark team or reports a problem with BoardMark itself'), explicit when-NOT ('never for the user's own project work — that is issues: create_issue, search_issues'), and a pre-condition naming an alternative action ('Check here before opening a case ... then reply there instead').

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