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

Annotations cover the safety profile (readOnlyHint=true, openWorldHint=false), and the description adds genuinely new behavioral context: the search spans every brand the user holds, every job carries its brand, and an ambiguous search returns `matches` instead of `job`. With no output schema, that polymorphic return disclosure is important. Only the empty-result/error behavior is left unstated.

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 core action is front-loaded in the first clause, and the second sentence handles the ambiguous-match case with no filler. The first sentence is dense, packing scope, three modes and brand semantics into one run-on, but nothing is wasted.

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?

Because there is no output schema, the description correctly spends its budget explaining the `job` vs `matches` response shape and the follow-up action for ambiguity. It is close to complete for a no-required-param lookup tool, missing only what happens when nothing matches.

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 100%, so job_id, search and job_number are already documented, and the description largely restates them. It adds little syntax or format guidance beyond echoing that search matches title and customer name; the baseline of 3 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 description gives a specific verb set (fetch/search) plus the resource (job) and the three lookup modes (number, id, free text), which cleanly separates it from create_job, cancel_job and the project/customer finders. It also states the scope ('in every brand the user holds'), a detail not derivable from the name alone.

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 implied rather than stated: an agent can infer 'look up a job' and the multi-match fallback ('ask the user which they mean'), but there is no explicit when-to-use versus siblings such as search, fetch, find_project or find_customer, and no statement of when this tool is the wrong choice.

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