Design Specifications (Specs)
Relevant source files
The following files were used as context for generating this wiki page:
- specs/001-create-a-comprehensive/spec.md
- kitty-specs/002-unquoted-cli-arguments/checklists/requirements.md
- specs/002-implement-tdd-green/spec.md
- specs/003-implement-core-infrastructure/spec.md
- specs/005-karo-distributed-mesh/spec.md
- specs/006-intelligent-prompt-generation/spec.md
- CONTRIBUTING.md
- specs/002-implement-tdd-green/plan.md
Design Specifications (Specs) are the foundation of the caro project's development process. Following a "spec-driven development" approach, every new feature begins with a detailed specification document. These documents serve as a single source of truth, defining the feature's purpose, user-facing behavior, technical requirements, and success criteria before any implementation code is written. This methodology ensures that all development work is aligned with clear, pre-defined goals, which is particularly critical for a security-focused tool like caro.
The spec-first approach mandates that a feature's requirements, user stories, and acceptance criteria are thoroughly documented and reviewed. This process is integral to the project's Test-Driven Development (TDD) workflow, where tests are written based on the spec to validate its requirements.
Sources: CONTRIBUTING.md:298-312, specs/002-implement-tdd-green/plan.md:1-8
Specification Structure
Each feature specification is contained within its own directory, typically under specs/[feature-id]/. These directories follow a consistent structure to organize all design artifacts related to the feature.
Sources: CONTRIBUTING.md:299-309
This diagram illustrates the typical file structure within a feature's spec directory.
A typical spec.md file is organized into several key sections:
- Overview/Executive Summary: A high-level summary of the feature, the problem it solves, and the proposed solution.
- User Stories: Descriptions of feature goals from an end-user perspective, framed as "As a [user type], I want [goal] so that [benefit]".
- Acceptance Scenarios: Concrete, testable scenarios that demonstrate the user stories.
- Functional Requirements (FR): A numbered list of specific behaviors the system MUST exhibit.
- Non-Functional Requirements (NFR): Constraints and quality attributes such as performance, security, and reliability.
- Key Entities/Data Models: Definitions of the primary data structures involved.
- Out of Scope: A clear boundary of what the feature will not include.
- Success Criteria: Measurable metrics that define a successful implementation.
Sources: specs/002-implement-tdd-green/spec.md, specs/006-intelligent-prompt-generation/spec.md, specs/005-karo-distributed-mesh/spec.md
Key Components of a Specification
User Stories and Acceptance Scenarios
User stories translate high-level goals into tangible user needs. Each story is accompanied by acceptance criteria and concrete scenarios that form the basis for integration and end-to-end tests.
For example, the "Ambiguity Detection & Clarification" feature includes a user story for handling vague user input. The acceptance criteria require the system to detect ambiguity, ask clarifying questions, and generate a command based on the user's answers.
Sources: specs/006-intelligent-prompt-generation/spec.md:69-96
Requirements (Functional and Non-Functional)
Requirements provide a detailed, testable breakdown of system behavior.
- Functional Requirements (FRs) define what the system does. For instance, the distributed mesh feature requires the system to generate an Ed25519 keypair on first startup (FR-101) and use TLS 1.3 for all communication (FR-201).
- Non-Functional Requirements (NFRs) define how the system should perform. These often relate to performance, security, and reliability.
The table below summarizes common NFRs found in caro specifications.
| Category | Requirement Example | Target |
|---|---|---|
| Performance | CLI startup time | < 100ms |
| Performance | Safety validation latency | < 50ms |
| Performance | Command generation (mock backend) | < 2s |
| Security | Cryptographic Operations | Use audited libraries (e.g., ring, rustls) |
| Security | Private Key Handling | Keys must never leave the local machine |
| Reliability | Peer Unavailability | Gracefully degrade when peers are unreachable |
| Code Quality | Documentation | All public APIs must have rustdoc comments |
Sources: specs/002-implement-tdd-green/spec.md:99-110, specs/005-karo-distributed-mesh/spec.md:200-220, specs/003-implement-core-infrastructure/spec.md:183-193
Data Models and Key Entities
Specs define the core data structures, or "Key Entities," that a feature will use. This ensures clarity on the data being manipulated before implementation begins. For example, the "Intelligent Prompt Generation" feature defines entities like ValidationResult to structure the output of the validation agent.
The diagram below shows the structure of the ValidationResult entity.
Success Criteria
Every specification concludes with a list of measurable success criteria. These are non-negotiable conditions that must be met for the feature to be considered complete. They often include test pass rates, performance benchmarks, and code quality metrics.
Example Success Criteria:
- All 80 contract tests pass.
- Performance targets for startup (<100ms) and validation (<50ms) are met.
- Code coverage for implemented modules is > 80%.
- No
clippywarnings are present. - TDD discipline is maintained (verified via git history).
Sources: specs/002-implement-tdd-green/spec.md:136-143
The Spec-Driven Development Workflow
The caro project follows a strict workflow that begins with a specification and moves through planning, testing, and implementation.
This flowchart illustrates the development lifecycle for a new feature.
A key part of this process is the Multi-Turn Validation Loop, where an initial command is generated, validated, and then regenerated with feedback if it fails.
This sequence diagram shows the multi-turn validation process.
Specification Quality and Validation
Before a specification can proceed to the planning phase, it must pass a rigorous quality check. This ensures that the requirements are complete, testable, and free of implementation details.
The following checklist is used to validate the quality of a specification.
| Area | Check | Status |
|---|---|---|
| Content Quality | No implementation details (languages, frameworks) | PASS ✓ |
| Focused on user value and business needs | PASS ✓ | |
| Written for non-technical stakeholders | PASS ✓ | |
| Requirement Completeness | No [NEEDS CLARIFICATION] markers remain | PASS ✓ |
| Requirements are testable and unambiguous | PASS ✓ | |
| Success criteria are measurable and technology-agnostic | PASS ✓ | |
| Edge cases are identified | PASS ✓ | |
| Feature Readiness | All functional requirements have clear acceptance criteria | PASS ✓ |
| Scope is clearly bounded with an "Out of Scope" section | PASS ✓ |
Sources: kitty-specs/002-unquoted-cli-arguments/checklists/requirements.md
Conclusion
The spec-driven development process is a cornerstone of the caro project's engineering philosophy. By defining "what" and "why" before "how," specifications ensure that every feature is built with a clear purpose, measurable goals, and a strong emphasis on quality and security. This structured approach allows for a robust TDD cycle, minimizes ambiguity, and provides a clear framework for both developers and external contributors to build a trustworthy and reliable tool.
Sources: CONTRIBUTING.md:298-312, specs/002-implement-tdd-green/plan.md:47-65