Bmad Nfr Assess

---
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:

1. `{skill-root}/customize.toml` — defaults
2. `{project-root}/_bmad/custom/{skill-name}.toml` — team overrides
3. `{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.

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**Activation complete.** Read FULLY and follow `./workflow.md` — load the file with the Read tool, do not summarise from memory, do not skip sections.