Create or update feature specifications from natural language descriptions. Use when starting new features or refining requirements. Generates spec.md with user stories, functional requirements, and acceptance criteria following spec-driven development methodology.
npx skills add https://github.com/foryourhealth111-pixel/Vibe-Skills --skill speckit-specify
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
The text the user typed after /speckit.specify in the triggering message is the feature description. Assume you always have it available in this conversation even if $ARGUMENTS appears literally below. Do not ask the user to repeat it unless they provided an empty command.
Given that feature description, do this:
a. First, fetch all remote branches to ensure we have the latest information:
git fetch --all --prune
b. Find the highest feature number across all sources for the short-name:
git ls-remote --heads origin | grep -E 'refs/heads/[0-9]+-<short-name>$'git branch | grep -E '^[* ]*[0-9]+-<short-name>$'specs/[0-9]+-<short-name>c. Determine the next available number:
d. Run the script .specify/scripts/powershell/create-new-feature.ps1 -Json "$ARGUMENTS" with the calculated number and short-name:
--number N+1 and --short-name "your-short-name" along with the feature description.specify/scripts/powershell/create-new-feature.ps1 -Json "$ARGUMENTS" --json --number 5 --short-name "user-auth" "Add user authentication".specify/scripts/powershell/create-new-feature.ps1 -Json "$ARGUMENTS" -Json -Number 5 -ShortName "user-auth" "Add user authentication"IMPORTANT:
.specify/templates/spec-template.md to understand required sections.If empty: ERROR "No feature description provided"
Identify: actors, actions, data, constraints
If no clear user flow: ERROR "Cannot determine user scenarios"
Each requirement must be testable
Use reasonable defaults for unspecified details (document assumptions in Assumptions section)
Create measurable, technology-agnostic outcomes
Include both quantitative metrics (time, performance, volume) and qualitative measures (user satisfaction, task completion)
Each criterion must be verifiable without implementation details
a. Create Spec Quality Checklist: Generate a checklist file at FEATURE_DIR/checklists/requirements.md using the checklist template structure with these validation items:
# Specification Quality Checklist: [FEATURE NAME]
**Purpose**: Validate specification completeness and quality before proceeding to planning
**Created**: [DATE]
**Feature**: [Link to spec.md]
## Content Quality
- [ ] No implementation details (languages, frameworks, APIs)
- [ ] Focused on user value and business needs
- [ ] Written for non-technical stakeholders
- [ ] All mandatory sections completed
## Requirement Completeness
- [ ] No [NEEDS CLARIFICATION] markers remain
- [ ] Requirements are testable and unambiguous
- [ ] Success criteria are measurable
- [ ] Success criteria are technology-agnostic (no implementation details)
- [ ] All acceptance scenarios are defined
- [ ] Edge cases are identified
- [ ] Scope is clearly bounded
- [ ] Dependencies and assumptions identified
## Feature Readiness
- [ ] All functional requirements have clear acceptance criteria
- [ ] User scenarios cover primary flows
- [ ] Feature meets measurable outcomes defined in Success Criteria
- [ ] No implementation details leak into specification
## Notes
- Items marked incomplete require spec updates before `/speckit.clarify` or `/speckit.plan`
b. Run Validation Check: Review the spec against each checklist item:
c. Handle Validation Results:
## Question [N]: [Topic]
**Context**: [Quote relevant spec section]
**What we need to know**: [Specific question from NEEDS CLARIFICATION marker]
**Suggested Answers**:
| Option | Answer | Implications |
|--------|--------|--------------|
| A | [First suggested answer] | [What this means for the feature] |
| B | [Second suggested answer] | [What this means for the feature] |
| C | [Third suggested answer] | [What this means for the feature] |
| Custom | Provide your own answer | [Explain how to provide custom input] |
**Your choice**: _[Wait for user response]_
| Content | not |Content||--------|d. Update Checklist: After each validation iteration, update the checklist file with current pass/fail status
/speckit.clarify or /speckit.plan).NOTE: The script creates and checks out the new branch and initializes the spec file before writing.
When creating this spec from a user prompt:
Examples of reasonable defaults (don't ask about these):
Success criteria must be:
Good examples:
Bad examples (implementation-focused):
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take foryourhealth111-pixel/speckit-specify from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.