linear_update_issue

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

No annotations provided. Description discloses it performs an update and returns a dictionary with updated details or error, but lacks detail on side effects, validation, or concurrency behavior. Adequate but not comprehensive.

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?

One-sentence purpose followed by a clear list of arguments and return value. No extraneous text, well-structured, and front-loaded.

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?

Given no output schema, the description states the return type (dictionary with updated details or error). Missing explicit mention of which fields are required (covered by schema), but overall sufficient for a simple update 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 description coverage is 0%, but the description compensates by explaining all 5 parameters with examples for issue_id, state, and priority, adding significant meaning beyond the schema's bare titles.

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?

Description explicitly states 'Update an existing Linear issue.' Uses a specific verb and resource, clearly distinguishing from siblings like linear_create_issue (create) and linear_get_issue (read).

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 implies when to use the tool (to update an existing issue) but does not explicitly exclude scenarios or mention prerequisites like issue existence. Clear context without exclusions.

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