Search issues (JQL)

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It reveals non-obvious platform-specific behaviors: enhanced vs legacy endpoint, rejection of unbounded JQL, absence of total on Cloud, cursor vs offset paging, and the optional approximateTotal request. This goes well beyond what the name or schema conveys.

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?

Every sentence earns its place: purpose with examples, Cloud-specific behavior, and Data Center-specific behavior. The description is structured with the core action first and platform differences clearly separated, with no filler or redundant restatement.

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 complex 7-parameter, dual-backend tool with no output schema, the description provides the critical operational details: bounded JQL requirement, paging contract, total behavior, and approximate total option. An agent has enough information to call the tool and page through results correctly on either platform.

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 high at 86%, giving the description a lower burden. Still, it adds meaningful parameter context: jql must be bounded, with explicit examples; startAt vs nextPageToken are tied to platform; includeApproximateTotal triggers an extra request. The remaining parameters are adequately covered by the schema.

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 states a specific action and resource: search issues using JQL, reinforced by two concrete query examples. It clearly differentiates from sibling tools like get_issue (single issue retrieval) and get_sprint_issues (sprint-scoped retrieval) by centering on arbitrary JQL search.

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?

The description gives clear operational context: JQL must be bounded on Cloud, paging differs by deployment, and there is a stop condition for cursor paging. It does not explicitly name sibling alternatives or when-not-to-use conditions, but the intended use case is unambiguous and the platform-specific constraints are well explained.

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