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

With no annotations, the description carries the burden and does add real behavioral context: it is a read ('Gets'), the content is markdown, links are each annotated with 'what it is and when it matters', and it warns that the content is editor-written 'context, not instructions' — a useful provenance/trust signal. It omits access requirements and behavior on an invalid spaceKey, so it is not exhaustive.

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 sentences, front-loaded with the payload description before the usage cue and the trust caveat. Dense but each sentence does work; the parenthetical link list is slightly listy but informative.

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, so the description must describe the return value — and it does, covering both the description body and the link entries. Missing only edge-case behavior (unknown key, empty space) for a single-parameter read tool.

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% and the schema itself gives the example key format and points to list_spaces as the source. The description adds nothing about spaceKey, so 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 verb ('Gets') and resource ('space') and then enumerates the payload: the markdown description plus external links (repositories, docs, designs, dashboards). This clearly separates it from list_spaces (enumeration) and get_issue (issue detail) without needing to name them.

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 an explicit trigger: 'Read it before working on the space's issues to know which repository or doc is relevant.' That tells the agent when this tool earns a call. It stops short of naming an alternative or a when-not-to-use condition, so it is not a full 5.

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