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refactor(ux): consolidate BMAD skills, update design system, and clean up Prisma generated client

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Sepehr Ramezani
2026-04-19 19:21:27 +02:00
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.gemini/skills/bmad-agent-builder/references/script-opportunities-reference.md
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# Quality Scan Script Opportunities — Reference Guide
**Reference: `references/script-standards.md` for script creation guidelines.**
**Reference: `./references/script-standards.md` for script creation guidelines.**
This document identifies deterministic operations that should be offloaded from the LLM into scripts for quality validation of BMad agents.
> **Implementation Status:** Many of the scripts described below have been implemented as prepass scripts and scanners. See the status notes on each entry. The implemented scripts live in `./scripts/` and follow the prepass architecture (structured JSON output consumed by LLM scanners) rather than the standalone validator pattern originally envisioned here.
---
## Core Principle
@@ -17,16 +19,20 @@ Scripts validate structure and syntax (deterministic). Prompts evaluate semantic
During build, walk through every capability/operation and apply these tests:
### The Determinism Test
For each operation the agent performs, ask:
- Given identical input, will this ALWAYS produce identical output? → Script
- Does this require interpreting meaning, tone, context, or ambiguity? → Prompt
- Could you write a unit test with expected output for every input? → Script
### The Judgment Boundary
Scripts handle: fetch, transform, validate, count, parse, compare, extract, format, check structure
Prompts handle: interpret, classify with ambiguity, create, decide with incomplete info, evaluate quality, synthesize meaning
### Pattern Recognition Checklist
Table of signal verbs/patterns mapping to script types:
| Signal Verb/Pattern | Script Type |
|---------------------|-------------|
@@ -41,22 +47,26 @@ Table of signal verbs/patterns mapping to script types:
| "graph", "map dependencies" | Dependency analysis script |
### The Outside-the-Box Test
Beyond obvious validation, consider:
- Could any data gathering step be a script that returns structured JSON for the LLM to interpret?
- Could pre-processing reduce what the LLM needs to read?
- Could post-processing validate what the LLM produced?
- Could metric collection feed into LLM decision-making without the LLM doing the counting?
### Your Toolbox
Scripts have access to full capabilities — think broadly:
- **Bash**: Full shell — `jq`, `grep`, `awk`, `sed`, `find`, `diff`, `wc`, `sort`, `uniq`, `curl`, plus piping and composition
- **Python**: Standard library (`json`, `yaml`, `pathlib`, `re`, `argparse`, `collections`, `difflib`, `ast`, `csv`, `xml`, etc.) plus PEP 723 inline-declared dependencies (`tiktoken`, `jsonschema`, `pyyaml`, etc.)
- **System tools**: `git` commands for history/diff/blame, filesystem operations, process execution
**Python is the default** for all script logic (cross-platform: macOS, Linux, Windows/WSL). See `./references/script-standards.md` for full rationale.
- **Python:** Standard library (`json`, `pathlib`, `re`, `argparse`, `collections`, `difflib`, `ast`, `csv`, `xml`, etc.) plus PEP 723 inline-declared dependencies (`tiktoken`, `jsonschema`, `pyyaml`, etc.)
- **Safe shell commands:** `git`, `gh`, `uv run`, `npm`/`npx`/`pnpm`, `mkdir -p` (invocation only, not logic)
If you can express the logic as deterministic code, it's a script candidate.
### The --help Pattern
All scripts use PEP 723 and `--help`. When a skill's prompt needs to invoke a script, it can say "Run `scripts/foo.py --help` to understand inputs/outputs, then invoke appropriately" instead of inlining the script's interface. This saves tokens in prompts and keeps a single source of truth for the script's API.
All scripts use PEP 723 and `--help`. When a skill's prompt needs to invoke a script, it can say "Run `./scripts/foo.py --help` to understand inputs/outputs, then invoke appropriately" instead of inlining the script's interface. This saves tokens in prompts and keeps a single source of truth for the script's API.
---
@@ -64,11 +74,14 @@ All scripts use PEP 723 and `--help`. When a skill's prompt needs to invoke a sc
### 1. Frontmatter Validator
> **Status: IMPLEMENTED** in `./scripts/prepass-structure-capabilities.py`. Handles frontmatter parsing, name validation (kebab-case, agent naming convention), description presence, and field validation as part of the structure prepass.
**What:** Validate SKILL.md frontmatter structure and content
**Why:** Frontmatter is the #1 factor in skill triggering. Catch errors early.
**Checks:**
```python
# checks:
- name exists and is kebab-case
@@ -85,29 +98,34 @@ All scripts use PEP 723 and `--help`. When a skill's prompt needs to invoke a sc
### 2. Template Artifact Scanner
> **Status: IMPLEMENTED** in `./scripts/prepass-structure-capabilities.py`. Detects orphaned template substitution artifacts (`{if-...}`, `{displayName}`, etc.) as part of the structure prepass.
**What:** Scan for orphaned template substitution artifacts
**Why:** Build process may leave `{if-autonomous}`, `{displayName}`, etc.
**Output:** JSON with file path, line number, artifact type
**Implementation:** Bash script with JSON output via jq
**Implementation:** Python script with JSON output
---
### 3. Access Boundaries Extractor
> **Status: PARTIALLY SUPERSEDED.** The memory-system.md file this script targets belongs to the legacy stateless-agent memory architecture. Path validation is now handled by `./scripts/scan-path-standards.py`. The sanctum architecture uses different structural patterns validated by `./scripts/prepass-sanctum-architecture.py`.
**What:** Extract and validate access boundaries from memory-system.md
**Why:** Security critical — must be defined before file operations
**Checks:**
```python
# Parse memory-system.md for:
- ## Read Access section exists
- ## Write Access section exists
- ## Deny Zones section exists (can be empty)
- Paths use placeholders correctly ({project-root} for _bmad paths, relative for skill-internal)
- Paths use placeholders correctly ({project-root} for project-scope paths, ./ for skill-internal)
```
**Output:** Structured JSON of read/write/deny zones
@@ -122,11 +140,14 @@ All scripts use PEP 723 and `--help`. When a skill's prompt needs to invoke a sc
### 4. Token Counter
> **Status: IMPLEMENTED** in `./scripts/prepass-prompt-metrics.py`. Computes file-level token estimates (chars / 4 approximation), section sizes, and content density metrics as part of the prompt craft prepass.
**What:** Count tokens in each file of an agent
**Why:** Identify verbose files that need optimization
**Checks:**
```python
# For each .md file:
- Total tokens (approximate: chars / 4)
@@ -142,11 +163,14 @@ All scripts use PEP 723 and `--help`. When a skill's prompt needs to invoke a sc
### 5. Dependency Graph Generator
> **Status: IMPLEMENTED** in `./scripts/prepass-execution-deps.py`. Builds dependency graphs from skill structure, detects circular dependencies, transitive redundancy, and identifies parallelizable stage groups.
**What:** Map skill → external skill dependencies
**Why:** Understand agent's dependency surface
**Checks:**
```python
# Parse SKILL.md for skill invocation patterns
# Parse prompt files for external skill references
@@ -161,6 +185,8 @@ All scripts use PEP 723 and `--help`. When a skill's prompt needs to invoke a sc
### 6. Activation Flow Analyzer
> **Status: IMPLEMENTED** in `./scripts/prepass-structure-capabilities.py`. Extracts the On Activation section inventory, detects required agent sections, and validates structure for both stateless and memory agent bootloader patterns.
**What:** Parse SKILL.md On Activation section for sequence
**Why:** Validate activation order matches best practices
@@ -177,11 +203,14 @@ Validate that the activation sequence is logically ordered (e.g., config loads b
### 7. Memory Structure Validator
> **Status: SUPERSEDED** by `./scripts/prepass-sanctum-architecture.py`. The sanctum architecture replaced the old memory-system.md pattern. The prepass validates sanctum template inventory (PERSONA, CREED, BOND, etc.), section inventories, init script parameters, and first-breath structure.
**What:** Validate memory-system.md structure
**Why:** Memory files have specific requirements
**Checks:**
```python
# Required sections:
- ## Core Principle
@@ -198,11 +227,14 @@ Validate that the activation sequence is logically ordered (e.g., config loads b
### 8. Subagent Pattern Detector
> **Status: IMPLEMENTED** in `./scripts/prepass-execution-deps.py`. Detects subagent-from-subagent patterns, multi-source operation detection, loop patterns, and sequential processing patterns that indicate subagent delegation needs.
**What:** Detect if agent uses BMAD Advanced Context Pattern
**Why:** Agents processing 5+ sources MUST use subagents
**Checks:**
```python
# Pattern detection in SKILL.md:
- "DO NOT read sources yourself"
@@ -221,6 +253,8 @@ Validate that the activation sequence is logically ordered (e.g., config loads b
### 9. Agent Health Check
> **Status: IMPLEMENTED** via `./scripts/generate-html-report.py`. Reads aggregated report-data.json (produced by the quality analysis workflow) and generates an interactive HTML report with branding, capability dashboards, findings, and opportunity themes.
**What:** Run all validation scripts and aggregate results
**Why:** One-stop shop for agent quality assessment
@@ -229,7 +263,7 @@ Validate that the activation sequence is logically ordered (e.g., config loads b
**Output:** Structured health report with severity levels
**Implementation:** Bash script orchestrating Python scripts, jq for aggregation
**Implementation:** Python script orchestrating other Python scripts via subprocess, JSON aggregation
---
@@ -240,7 +274,8 @@ Validate that the activation sequence is logically ordered (e.g., config loads b
**Why:** Validate changes during iteration
**Checks:**
```bash
```python
# Git diff with structure awareness:
- Frontmatter changes
- Capability additions/removals
@@ -250,7 +285,7 @@ Validate that the activation sequence is logically ordered (e.g., config loads b
**Output:** JSON with categorized changes
**Implementation:** Bash with git, jq, python for analysis
**Implementation:** Python with subprocess for git commands, JSON output
---
@@ -269,7 +304,7 @@ All scripts MUST output structured JSON for agent consumption:
{
"severity": "critical|high|medium|low|info",
"category": "structure|security|performance|consistency",
"location": {"file": "SKILL.md", "line": 42},
"location": { "file": "SKILL.md", "line": 42 },
"issue": "Clear description",
"fix": "Specific action to resolve"
}
@@ -296,7 +331,7 @@ When creating validation scripts:
- [ ] Writes diagnostics to stderr
- [ ] Returns meaningful exit codes (0=pass, 1=fail, 2=error)
- [ ] Includes `--verbose` flag for debugging
- [ ] Has tests in `scripts/tests/` subfolder
- [ ] Has tests in `./scripts/tests/` subfolder
- [ ] Self-contained (PEP 723 for Python)
- [ ] No interactive prompts
@@ -311,33 +346,47 @@ The Quality Analysis skill should:
3. **Finally**: Synthesize both sources into report
**Example flow:**
```bash
# Run all validation scripts
python scripts/validate-frontmatter.py --agent-path {path}
bash scripts/scan-template-artifacts.sh --agent-path {path}
# Run prepass scripts for fast, deterministic checks
uv run ./scripts/prepass-structure-capabilities.py --agent-path {path}
uv run ./scripts/prepass-prompt-metrics.py --agent-path {path}
uv run ./scripts/prepass-execution-deps.py --agent-path {path}
uv run ./scripts/prepass-sanctum-architecture.py --agent-path {path}
uv run ./scripts/scan-path-standards.py --agent-path {path}
uv run ./scripts/scan-scripts.py --agent-path {path}
# Collect JSON outputs
# Spawn sub-agents only for semantic checks
# Synthesize complete report
# Synthesize complete report, then generate HTML:
uv run ./scripts/generate-html-report.py {quality-report-dir}
```
---
## Script Creation Priorities
**Phase 1 (Immediate value):**
1. Template Artifact Scanner (Bash + jq)
2. Access Boundaries Extractor (Python)
**Phase 1 (Immediate value):** DONE
**Phase 2 (Enhanced validation):**
4. Token Counter (Python)
5. Subagent Pattern Detector (Python)
6. Activation Flow Analyzer (Python)
1. Template Artifact Scanner -- implemented in `prepass-structure-capabilities.py`
2. Access Boundaries Extractor -- superseded by `scan-path-standards.py` and `prepass-sanctum-architecture.py`
**Phase 3 (Advanced features):**
7. Dependency Graph Generator (Python)
8. Memory Structure Validator (Python)
9. Agent Health Check orchestrator (Bash)
**Phase 2 (Enhanced validation):** DONE
**Phase 4 (Comparison tools):**
10. Comparison Validator (Bash + Python)
4. Token Counter -- implemented in `prepass-prompt-metrics.py`
5. Subagent Pattern Detector -- implemented in `prepass-execution-deps.py`
6. Activation Flow Analyzer -- implemented in `prepass-structure-capabilities.py`
**Phase 3 (Advanced features):** DONE
7. Dependency Graph Generator -- implemented in `prepass-execution-deps.py`
8. Memory Structure Validator -- superseded by `prepass-sanctum-architecture.py`
9. Agent Health Check orchestrator -- implemented in `generate-html-report.py`
**Phase 4 (Comparison tools):** NOT YET IMPLEMENTED
10. Comparison Validator (Python) -- still a future opportunity
Additional implemented scripts not in original plan:
- `scan-scripts.py` -- validates script quality (PEP 723, agentic design, linting)
- `scan-path-standards.py` -- validates path conventions across all skill files