pylon_update_issue

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the tool updates an existing issue, it fails to disclose critical behavioral traits such as required permissions, whether changes are reversible, rate limits, or what happens to unspecified fields. For a mutation tool with zero annotation coverage, this is a significant gap.

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 description is appropriately sized and front-loaded, with two sentences that efficiently convey the tool's purpose and usage. Every sentence earns its place by providing essential information without redundancy or unnecessary details.

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 the tool's complexity (mutation operation with 6 parameters) and lack of annotations and output schema, the description is incomplete. It adequately covers the purpose and basic usage but fails to address behavioral aspects like permissions, side effects, or response format, leaving gaps for an AI agent to operate safely and effectively.

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 the schema already documents all 6 parameters with examples and constraints. The description adds marginal value by listing some parameter purposes (e.g., 'change status', 'reassign to different team members'), but doesn't provide additional syntax or format details beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 clearly states the tool's purpose with specific verb ('Update') and resource ('existing support issue/ticket'), and distinguishes it from siblings like pylon_create_issue (for creation) and pylon_get_issue (for retrieval). It explicitly lists key operations like changing status, reassigning, updating priority, or modifying details.

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 provides clear context for when to use this tool ('as you work on the issue') and implies usage for updating existing issues, distinguishing it from creation tools. However, it lacks explicit exclusions or alternatives (e.g., when not to use vs. pylon_snooze_issue or pylon_search_issues), which prevents a perfect score.

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