Create GitHub Issue Set

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

Annotations indicate readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true. The description adds critical behavioral details: dryRun defaults to true for safety, the dry-run output includes per-issue preview, warnings for missing labels/bodies/titles exceeding limit, and the exact repo coordinates. It also describes return values for both dry-run and live creation. No contradictions.

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 well-structured: a one-line purpose, a safety note, a detailed explanation of dry-run output, and an 'Args' list. Every sentence adds value. No unnecessary words. Suitable length for an AI agent to quickly parse.

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 parameter count (5, 1 required), schema coverage (100%), and presence of output schema, the description fully covers the tool's behavior. It explains purpose, safety, parameter details, and return values. An agent can correctly select and invoke this tool with the provided information.

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%, but the description adds value beyond the schema: it explains the safety implication of dryRun default, notes that issues can directly accept plan_from_context's issueDrafts, and describes the return format. The 'Args' section provides clear, concise parameter descriptions that complement 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?

Description clearly states 'Split an SDLC plan into GitHub issues' – a specific verb and resource. The title 'Create GitHub Issue Set' reinforces this. Distinguishes from siblings like plan_from_context (which creates the plan) and prepare_work_item (which prepares but doesn't create issues).

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?

Explicit guidance on dryRun defaulting to true and the requirement to pass dryRun:false for actual creation. The description explains the dry-run output as a human confirmation page. However, it does not directly compare with sibling tools, though the context is clear enough for an agent to infer when to use this tool (after plan_from_context).

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