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jthom233
by jthom233

speckit_checklist

Create a requirement quality checklist for a feature, evaluating spec completeness, clarity, coverage, and consistency. Saves the checklist to the project's specs directory.

Instructions

Create a requirement quality checklist for a feature. Generates checklists that assess spec quality (completeness, clarity, coverage, consistency) — not implementation status. Saved to specs/{feature}/checklists/{name}.md.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentNoChecklist content in markdown. If omitted, creates from template.
feature_nameYesName of the feature.
project_pathNoPath to the spec-kit project root.
checklist_nameNoDescriptive name for the checklist (e.g., requirements, api, security). Saved as checklists/{checklist_name}.md.
checklist_typeNoDeprecated alias for checklist_name.
Behavior4/5

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

With no annotations, the description carries the burden. It discloses a key side effect: 'Saved to specs/{feature}/checklists/{name}.md,' making clear this is a write operation. It also scopes the tool's behavior to spec quality assessment, not implementation status. This is useful behavioral context, though it doesn't mention permissions or exact return behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences and front-loaded with the primary action. Every clause adds value: purpose, scope (spec quality vs implementation), and file location. No redundant or filler text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters and no output schema, the description covers the essential job: what it creates, where it saves, and what it doesn't do. It doesn't explain return values or the template fallback behavior, but the schema covers parameter details and the description is reasonably complete for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are already documented. The description adds value by explaining the output path pattern using feature_name and checklist_name, which helps the agent understand how these parameters interact. It also notes that content is optional, though this is only in the schema, not the description itself.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Create a requirement quality checklist for a feature.' It specifies the resource (a checklist) and the action (create), and further differentiates by clarifying it assesses 'spec quality (completeness, clarity, coverage, consistency) — not implementation status,' distinguishing it from related tools like speckit_check.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for use: when you need a quality checklist for a feature's spec. It also provides a negative guideline ('not implementation status'), which helps avoid misuse. However, it does not name specific sibling alternatives, so it stops short of explicit alternative comparison.

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

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