speckit_tasks_to_issues

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'creates corresponding GitHub issues,' which is a significant side effect, but does not mention authentication requirements, potential idempotency issues, whether it modifies tasks.md, or any failure modes. The behavior is largely obvious from the name, and the description adds only minimal context beyond that.

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 two sentences long, front-loaded with the core action, and contains no fluff. Every sentence earns its place: the first gives a concise summary, the second clarifies the exact mechanism (reads tasks.md). This is appropriately sized for the tool's simplicity.

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 moderate complexity (4 parameters, all schema-documented) and no output schema, the description is minimal but not fully complete. It does not mention return values (e.g., what happens after creation), error cases, or the fact that dry_run defaults to true. While the schema covers parameter details, the absence of annotation and output schema leaves gaps that a fuller description could fill.

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?

The input schema covers all four parameters with descriptions (100% coverage), so the baseline is 3. The tool description itself does not add any parameter-specific meaning—it does not explain feature_name, dry_run, labels, or project_path beyond what the schema already states. Since the schema handles parameter semantics well, no deduction is needed, but no extra credit is given either.

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: converting spec-kit tasks to GitHub issues, specifically reading tasks.md and creating corresponding issues. The verb 'convert' and the explicit resource ('spec-kit tasks' to 'GitHub issues') make it distinct from sibling tools like speckit_tasks or speckit_plan, which focus on task generation or planning rather than issue creation.

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 usage (when you have tasks and want GitHub issues) but does not explicitly state when to use this tool versus alternatives. It neither names alternatives like speckit_tasks (which might generate tasks) nor provides exclusion criteria. The lack of explicit guidance on prerequisites or sequencing relative to sibling tools leaves this dimension at a basic level.

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