| name | bmad-nfr-assess |
| description | Assesses Non-Functional Requirements (security, performance, reliability, maintainability, observability) with evidence-based codebase analysis. Scans actual code for patterns, scores each aspect, and produces a structured assessment saved as a tracker document. Supports epic-level (specific project) or system-level (whole codebase) scope. Use when 'nfr assess', 'nfr assessment', 'non functional', 'évaluation nfr', 'exigences non fonctionnelles', 'testarch nfr', 'testability assessment', 'test engineering nfr' is mentioned. |
| disable-model-invocation | true |
NFR Assess
Overview
Assesses Non-Functional Requirements (security, performance, reliability, maintainability, observability) with evidence-based codebase analysis.
Conventions
- Bare paths (e.g.
steps/step-01-init.md) resolve from the skill root.
{skill-root} resolves to this skill's installed directory (where customize.toml lives).{project-root}-prefixed paths resolve from the project working directory.{skill-name} resolves to the skill directory's basename.
On Activation
Step 1: Resolve the Workflow Block
Run: python3 ~/.claude/skills/bmad-shared/scripts/resolve_customization.py --skill {skill-root} --key workflow
If the script fails, resolve the workflow block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:
{skill-root}/customize.toml — defaults{project-root}/_bmad/custom/{skill-name}.toml — team overrides{project-root}/_bmad/custom/{skill-name}.user.toml — personal overrides
Any missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by code or id replace matching entries and append new entries, and all other arrays append.
Step 2: Execute Prepend Steps
Execute each entry in {workflow.activation_steps_prepend} in order before proceeding.
Step 3: Load Persistent Facts
Treat every entry in {workflow.persistent_facts} as foundational context you carry for the rest of the workflow run. Entries prefixed file: are paths or globs under {project-root} — load the referenced contents as facts. All other entries are facts verbatim.
Step 4: Load Project Workflow Context
Resolve the main project root (worktree-aware): run MAIN_PROJECT_ROOT=$(dirname "$(git rev-parse --git-common-dir)").
Load {MAIN_PROJECT_ROOT}/.claude/workflow-context.md and resolve from its YAML frontmatter:
- Use
{user_name} for greeting
- Use
{communication_language} for all communications
- Use
{document_output_language} for output documents
- Use
{planning_artifacts} for output location and artifact scanning
- Use
{project_knowledge} for additional context scanning
If workflow-context.md is missing, ask the user for their name and preferred language, then continue.
Step 5: Greet the User
Greet {user_name}, speaking in {communication_language}. Be warm but efficient.
Step 6: Execute Append Steps
Execute each entry in {workflow.activation_steps_append} in order.
Activation complete. Read FULLY and follow ./workflow.md — load the file with the Read tool, do not summarise from memory, do not skip sections.
