* chore: update gitignore for audit reports and playwright cache * fix: add YAML frontmatter (name + description) to all SKILL.md files - Added frontmatter to 34 skills that were missing it entirely (0% Tessl score) - Fixed name field format to kebab-case across all 169 skills - Resolves #284 * chore: sync codex skills symlinks [automated] * fix: optimize 14 low-scoring skills via Tessl review (#290) Tessl optimization: 14 skills improved from ≤69% to 85%+. Closes #285, #286. * chore: sync codex skills symlinks [automated] * fix: optimize 18 skills via Tessl review + compliance fix (closes #287) (#291) Phase 1: 18 skills optimized via Tessl (avg 77% → 95%). Closes #287. * feat: add scripts and references to 4 prompt-only skills + Tessl optimization (#292) Phase 2: 3 new scripts + 2 reference files for prompt-only skills. Tessl 45-55% → 94-100%. * feat: add 6 agents + 5 slash commands for full coverage (v2.7.0) (#293) Phase 3: 6 new agents (all 9 categories covered) + 5 slash commands. * fix: Phase 5 verification fixes + docs update (#294) Phase 5 verification fixes * chore: sync codex skills symlinks [automated] * fix: marketplace audit — all 11 plugins validated by Claude Code (#295) Marketplace audit: all 11 plugins validated + installed + tested in Claude Code * fix: restore 7 removed plugins + revert playwright-pro name to pw Reverts two overly aggressive audit changes: - Restored content-creator, demand-gen, fullstack-engineer, aws-architect, product-manager, scrum-master, skill-security-auditor to marketplace - Reverted playwright-pro plugin.json name back to 'pw' (intentional short name) * refactor: split 21 over-500-line skills into SKILL.md + references (#296) * chore: sync codex skills symlinks [automated] * docs: update all documentation with accurate counts and regenerated skill pages - Update skill count to 170, Python tools to 213, references to 314 across all docs - Regenerate all 170 skill doc pages from latest SKILL.md sources - Update CLAUDE.md with v2.1.1 highlights, accurate architecture tree, and roadmap - Update README.md badges and overview table - Update marketplace.json metadata description and version - Update mkdocs.yml, index.md, getting-started.md with correct numbers * fix: add root-level SKILL.md and .codex/instructions.md to all domains (#301) Root cause: CLI tools (ai-agent-skills, agent-skills-cli) look for SKILL.md at the specified install path. 7 of 9 domain directories were missing this file, causing "Skill not found" errors for bundle installs like: npx ai-agent-skills install alirezarezvani/claude-skills/engineering-team Fix: - Add root-level SKILL.md with YAML frontmatter to 7 domains - Add .codex/instructions.md to 8 domains (for Codex CLI discovery) - Update INSTALLATION.md with accurate skill counts (53→170) - Add troubleshooting entry for "Skill not found" error All 9 domains now have: SKILL.md + .codex/instructions.md + plugin.json Closes #301 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add Gemini CLI + OpenClaw support, fix Codex missing 25 skills Gemini CLI: - Add GEMINI.md with activation instructions - Add scripts/gemini-install.sh setup script - Add scripts/sync-gemini-skills.py (194 skills indexed) - Add .gemini/skills/ with symlinks for all skills, agents, commands - Remove phantom medium-content-pro entries from sync script - Add top-level folder filter to prevent gitignored dirs from leaking Codex CLI: - Fix sync-codex-skills.py missing "engineering" domain (25 POWERFUL skills) - Regenerate .codex/skills-index.json: 124 → 149 skills - Add 25 new symlinks in .codex/skills/ OpenClaw: - Add OpenClaw installation section to INSTALLATION.md - Add ClawHub install + manual install + YAML frontmatter docs Documentation: - Update INSTALLATION.md with all 4 platforms + accurate counts - Update README.md: "three platforms" → "four platforms" + Gemini quick start - Update CLAUDE.md with Gemini CLI support in v2.1.1 highlights - Update SKILL-AUTHORING-STANDARD.md + SKILL_PIPELINE.md with Gemini steps - Add OpenClaw + Gemini to installation locations reference table Marketplace: all 18 plugins validated — sources exist, SKILL.md present Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(product,pm): world-class product & PM skills audit — 6 scripts, 5 agents, 7 commands, 23 references/assets Phase 1 — Agent & Command Foundation: - Rewrite cs-project-manager agent (55→515 lines, 4 workflows, 6 skill integrations) - Expand cs-product-manager agent (408→684 lines, orchestrates all 8 product skills) - Add 7 slash commands: /rice, /okr, /persona, /user-story, /sprint-health, /project-health, /retro Phase 2 — Script Gap Closure (2,779 lines): - jira-expert: jql_query_builder.py (22 patterns), workflow_validator.py - confluence-expert: space_structure_generator.py, content_audit_analyzer.py - atlassian-admin: permission_audit_tool.py - atlassian-templates: template_scaffolder.py (Confluence XHTML generation) Phase 3 — Reference & Asset Enrichment: - 9 product references (competitive-teardown, landing-page-generator, saas-scaffolder) - 6 PM references (confluence-expert, atlassian-admin, atlassian-templates) - 7 product assets (templates for PRD, RICE, sprint, stories, OKR, research, design system) - 1 PM asset (permission_scheme_template.json) Phase 4 — New Agents: - cs-agile-product-owner, cs-product-strategist, cs-ux-researcher Phase 5 — Integration & Polish: - Related Skills cross-references in 8 SKILL.md files - Updated product-team/CLAUDE.md (5→8 skills, 6→9 tools, 4 agents, 5 commands) - Updated project-management/CLAUDE.md (0→12 scripts, 3 commands) - Regenerated docs site (177 pages), updated homepage and getting-started Quality audit: 31 files reviewed, 29 PASS, 2 fixed (copy-frameworks.md, governance-framework.md) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: audit and repair all plugins, agents, and commands - Fix 12 command files: correct CLI arg syntax, script paths, and usage docs - Fix 3 agents with broken script/reference paths (cs-content-creator, cs-demand-gen-specialist, cs-financial-analyst) - Add complete YAML frontmatter to 5 agents (cs-growth-strategist, cs-engineering-lead, cs-senior-engineer, cs-financial-analyst, cs-quality-regulatory) - Fix cs-ceo-advisor related agent path - Update marketplace.json metadata counts (224 tools, 341 refs, 14 agents, 12 commands) Verified: all 19 scripts pass --help, all 14 agent paths resolve, mkdocs builds clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: repair 25 Python scripts failing --help across all domains - Fix Python 3.10+ syntax (float | None → Optional[float]) in 2 scripts - Add argparse CLI handling to 9 marketing scripts using raw sys.argv - Fix 10 scripts crashing at module level (wrap in __main__, add argparse) - Make yaml/prefect/mcp imports conditional with stdlib fallbacks (4 scripts) - Fix f-string backslash syntax in project_bootstrapper.py - Fix -h flag conflict in pr_analyzer.py - Fix tech-debt.md description (score → prioritize) All 237 scripts now pass python3 --help verification. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(product-team): close 3 verified gaps in product skills - Fix competitive-teardown/SKILL.md: replace broken references DATA_COLLECTION.md → references/data-collection-guide.md and TEMPLATES.md → references/analysis-templates.md (workflow was broken at steps 2 and 4) - Upgrade landing_page_scaffolder.py: add TSX + Tailwind output format (--format tsx) matching SKILL.md promise of Next.js/React components. 4 design styles (dark-saas, clean-minimal, bold-startup, enterprise). TSX is now default; HTML preserved via --format html - Rewrite README.md: fix stale counts (was 5 skills/15+ tools, now accurately shows 8 skills/9 tools), remove 7 ghost scripts that never existed (sprint_planner.py, velocity_tracker.py, etc.) - Fix tech-debt.md description (score → prioritize) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * release: v2.1.2 — landing page TSX output, brand voice integration, docs update - Landing page generator defaults to Next.js TSX + Tailwind CSS (4 design styles) - Brand voice analyzer integrated into landing page generation workflow - CHANGELOG, CLAUDE.md, README.md updated for v2.1.2 - All 13 plugin.json + marketplace.json bumped to 2.1.2 - Gemini/Codex skill indexes re-synced - Backward compatible: --format html preserved, no breaking changes Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: alirezarezvani <5697919+alirezarezvani@users.noreply.github.com> Co-authored-by: Leo <leo@openclaw.ai> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
425 lines
14 KiB
Python
425 lines
14 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
Workflow Validator
|
|
|
|
Validates Jira workflow definitions (JSON input) for anti-patterns and common
|
|
issues. Checks for dead-end states, orphan states, missing transitions, circular
|
|
paths, and produces a health score with severity-rated findings.
|
|
|
|
Usage:
|
|
python workflow_validator.py workflow.json
|
|
python workflow_validator.py workflow.json --format json
|
|
"""
|
|
|
|
import argparse
|
|
import json
|
|
import sys
|
|
from typing import Any, Dict, List, Optional, Set, Tuple
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Validation Configuration
|
|
# ---------------------------------------------------------------------------
|
|
|
|
MAX_RECOMMENDED_STATES = 10
|
|
REQUIRED_TERMINAL_STATES = {"done", "closed", "resolved", "completed"}
|
|
|
|
SEVERITY_WEIGHTS = {
|
|
"error": 20,
|
|
"warning": 10,
|
|
"info": 3,
|
|
}
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Validation Rules
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def check_state_count(states: List[str]) -> List[Dict[str, str]]:
|
|
"""Check if the workflow has too many states."""
|
|
findings = []
|
|
count = len(states)
|
|
|
|
if count > MAX_RECOMMENDED_STATES:
|
|
findings.append({
|
|
"rule": "state_count",
|
|
"severity": "warning",
|
|
"message": f"Workflow has {count} states (recommended max: {MAX_RECOMMENDED_STATES}). "
|
|
f"Complex workflows slow teams down and increase error rates.",
|
|
})
|
|
elif count < 2:
|
|
findings.append({
|
|
"rule": "state_count",
|
|
"severity": "error",
|
|
"message": f"Workflow has only {count} state(s). A minimum of 2 states is required.",
|
|
})
|
|
|
|
if count > 15:
|
|
findings[-1]["severity"] = "error"
|
|
|
|
return findings
|
|
|
|
|
|
def check_dead_end_states(
|
|
states: List[str],
|
|
transitions: List[Dict[str, str]],
|
|
terminal_states: Set[str],
|
|
) -> List[Dict[str, str]]:
|
|
"""Find states with no outgoing transitions that are not terminal."""
|
|
findings = []
|
|
outgoing = set()
|
|
for t in transitions:
|
|
outgoing.add(t.get("from", "").lower())
|
|
|
|
for state in states:
|
|
state_lower = state.lower()
|
|
if state_lower not in outgoing and state_lower not in terminal_states:
|
|
findings.append({
|
|
"rule": "dead_end_state",
|
|
"severity": "error",
|
|
"message": f"State '{state}' has no outgoing transitions and is not a terminal state. "
|
|
f"Issues will get stuck here.",
|
|
})
|
|
|
|
return findings
|
|
|
|
|
|
def check_orphan_states(
|
|
states: List[str],
|
|
transitions: List[Dict[str, str]],
|
|
initial_state: Optional[str],
|
|
) -> List[Dict[str, str]]:
|
|
"""Find states with no incoming transitions (except the initial state)."""
|
|
findings = []
|
|
incoming = set()
|
|
for t in transitions:
|
|
incoming.add(t.get("to", "").lower())
|
|
|
|
initial_lower = (initial_state or "").lower()
|
|
|
|
for state in states:
|
|
state_lower = state.lower()
|
|
if state_lower not in incoming and state_lower != initial_lower:
|
|
findings.append({
|
|
"rule": "orphan_state",
|
|
"severity": "warning",
|
|
"message": f"State '{state}' has no incoming transitions and is not the initial state. "
|
|
f"This state may be unreachable.",
|
|
})
|
|
|
|
return findings
|
|
|
|
|
|
def check_missing_terminal_state(states: List[str]) -> List[Dict[str, str]]:
|
|
"""Check that at least one terminal/done state exists."""
|
|
findings = []
|
|
states_lower = {s.lower() for s in states}
|
|
|
|
has_terminal = bool(states_lower & REQUIRED_TERMINAL_STATES)
|
|
if not has_terminal:
|
|
findings.append({
|
|
"rule": "missing_terminal_state",
|
|
"severity": "error",
|
|
"message": f"No terminal state found. Expected one of: {', '.join(sorted(REQUIRED_TERMINAL_STATES))}. "
|
|
f"Issues cannot be marked as complete.",
|
|
})
|
|
|
|
return findings
|
|
|
|
|
|
def check_duplicate_transition_names(
|
|
transitions: List[Dict[str, str]],
|
|
) -> List[Dict[str, str]]:
|
|
"""Check for duplicate transition names from the same state."""
|
|
findings = []
|
|
seen = {}
|
|
|
|
for t in transitions:
|
|
name = t.get("name", "").lower()
|
|
from_state = t.get("from", "").lower()
|
|
key = (from_state, name)
|
|
|
|
if key in seen:
|
|
findings.append({
|
|
"rule": "duplicate_transition",
|
|
"severity": "warning",
|
|
"message": f"Duplicate transition name '{t.get('name', '')}' from state '{t.get('from', '')}'. "
|
|
f"This can confuse users selecting transitions.",
|
|
})
|
|
else:
|
|
seen[key] = True
|
|
|
|
return findings
|
|
|
|
|
|
def check_missing_transitions(
|
|
states: List[str],
|
|
transitions: List[Dict[str, str]],
|
|
) -> List[Dict[str, str]]:
|
|
"""Check for states referenced in transitions but not defined."""
|
|
findings = []
|
|
defined_states = {s.lower() for s in states}
|
|
|
|
for t in transitions:
|
|
from_state = t.get("from", "").lower()
|
|
to_state = t.get("to", "").lower()
|
|
|
|
if from_state and from_state not in defined_states:
|
|
findings.append({
|
|
"rule": "undefined_state_reference",
|
|
"severity": "error",
|
|
"message": f"Transition references undefined source state '{t.get('from', '')}'.",
|
|
})
|
|
|
|
if to_state and to_state not in defined_states:
|
|
findings.append({
|
|
"rule": "undefined_state_reference",
|
|
"severity": "error",
|
|
"message": f"Transition references undefined target state '{t.get('to', '')}'.",
|
|
})
|
|
|
|
return findings
|
|
|
|
|
|
def check_circular_paths(
|
|
states: List[str],
|
|
transitions: List[Dict[str, str]],
|
|
terminal_states: Set[str],
|
|
) -> List[Dict[str, str]]:
|
|
"""Detect circular paths that have no exit to a terminal state."""
|
|
findings = []
|
|
|
|
# Build adjacency list
|
|
adjacency = {}
|
|
for state in states:
|
|
adjacency[state.lower()] = set()
|
|
for t in transitions:
|
|
from_state = t.get("from", "").lower()
|
|
to_state = t.get("to", "").lower()
|
|
if from_state in adjacency:
|
|
adjacency[from_state].add(to_state)
|
|
|
|
# Find strongly connected components using iterative DFS
|
|
def can_reach_terminal(start: str) -> bool:
|
|
visited = set()
|
|
stack = [start]
|
|
while stack:
|
|
node = stack.pop()
|
|
if node in terminal_states:
|
|
return True
|
|
if node in visited:
|
|
continue
|
|
visited.add(node)
|
|
for neighbor in adjacency.get(node, set()):
|
|
stack.append(neighbor)
|
|
return False
|
|
|
|
# Check each non-terminal state
|
|
for state in states:
|
|
state_lower = state.lower()
|
|
if state_lower not in terminal_states:
|
|
if not can_reach_terminal(state_lower):
|
|
findings.append({
|
|
"rule": "circular_no_exit",
|
|
"severity": "error",
|
|
"message": f"State '{state}' cannot reach any terminal state. "
|
|
f"Issues entering this state will never be resolved.",
|
|
})
|
|
|
|
return findings
|
|
|
|
|
|
def check_self_transitions(transitions: List[Dict[str, str]]) -> List[Dict[str, str]]:
|
|
"""Check for transitions that go from a state to itself."""
|
|
findings = []
|
|
for t in transitions:
|
|
if t.get("from", "").lower() == t.get("to", "").lower():
|
|
findings.append({
|
|
"rule": "self_transition",
|
|
"severity": "info",
|
|
"message": f"State '{t.get('from', '')}' has a self-transition '{t.get('name', '')}'. "
|
|
f"Ensure this is intentional (e.g., for triggering automation).",
|
|
})
|
|
return findings
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Main Validation
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def validate_workflow(data: Dict[str, Any]) -> Dict[str, Any]:
|
|
"""Run all validations on a workflow definition."""
|
|
states = data.get("states", [])
|
|
transitions = data.get("transitions", [])
|
|
initial_state = data.get("initial_state", states[0] if states else None)
|
|
|
|
if not states:
|
|
return {
|
|
"health_score": 0,
|
|
"grade": "invalid",
|
|
"findings": [{"rule": "no_states", "severity": "error", "message": "No states defined in workflow"}],
|
|
"summary": {"errors": 1, "warnings": 0, "info": 0},
|
|
}
|
|
|
|
# Determine terminal states
|
|
states_lower = {s.lower() for s in states}
|
|
terminal_states = states_lower & REQUIRED_TERMINAL_STATES
|
|
|
|
# Custom terminal states from input
|
|
custom_terminals = data.get("terminal_states", [])
|
|
for ct in custom_terminals:
|
|
terminal_states.add(ct.lower())
|
|
|
|
# Run all checks
|
|
all_findings = []
|
|
all_findings.extend(check_state_count(states))
|
|
all_findings.extend(check_dead_end_states(states, transitions, terminal_states))
|
|
all_findings.extend(check_orphan_states(states, transitions, initial_state))
|
|
all_findings.extend(check_missing_terminal_state(states))
|
|
all_findings.extend(check_duplicate_transition_names(transitions))
|
|
all_findings.extend(check_missing_transitions(states, transitions))
|
|
all_findings.extend(check_circular_paths(states, transitions, terminal_states))
|
|
all_findings.extend(check_self_transitions(transitions))
|
|
|
|
# Calculate health score
|
|
summary = {"errors": 0, "warnings": 0, "info": 0}
|
|
penalty = 0
|
|
for finding in all_findings:
|
|
severity = finding["severity"]
|
|
summary[severity] = summary.get(severity, 0) + 1
|
|
penalty += SEVERITY_WEIGHTS.get(severity, 0)
|
|
|
|
health_score = max(0, 100 - penalty)
|
|
|
|
if health_score >= 90:
|
|
grade = "excellent"
|
|
elif health_score >= 75:
|
|
grade = "good"
|
|
elif health_score >= 55:
|
|
grade = "fair"
|
|
else:
|
|
grade = "poor"
|
|
|
|
return {
|
|
"health_score": health_score,
|
|
"grade": grade,
|
|
"findings": all_findings,
|
|
"summary": summary,
|
|
"workflow_info": {
|
|
"state_count": len(states),
|
|
"transition_count": len(transitions),
|
|
"initial_state": initial_state,
|
|
"terminal_states": sorted(terminal_states),
|
|
},
|
|
}
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Output Formatting
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def format_text_output(result: Dict[str, Any]) -> str:
|
|
"""Format results as readable text report."""
|
|
lines = []
|
|
lines.append("=" * 60)
|
|
lines.append("WORKFLOW VALIDATION REPORT")
|
|
lines.append("=" * 60)
|
|
lines.append("")
|
|
|
|
# Health summary
|
|
lines.append("HEALTH SUMMARY")
|
|
lines.append("-" * 30)
|
|
lines.append(f"Health Score: {result['health_score']}/100")
|
|
lines.append(f"Grade: {result['grade'].title()}")
|
|
lines.append("")
|
|
|
|
# Workflow info
|
|
info = result.get("workflow_info", {})
|
|
if info:
|
|
lines.append("WORKFLOW INFO")
|
|
lines.append("-" * 30)
|
|
lines.append(f"States: {info.get('state_count', 0)}")
|
|
lines.append(f"Transitions: {info.get('transition_count', 0)}")
|
|
lines.append(f"Initial State: {info.get('initial_state', 'N/A')}")
|
|
lines.append(f"Terminal States: {', '.join(info.get('terminal_states', []))}")
|
|
lines.append("")
|
|
|
|
# Summary
|
|
summary = result.get("summary", {})
|
|
lines.append("FINDINGS SUMMARY")
|
|
lines.append("-" * 30)
|
|
lines.append(f"Errors: {summary.get('errors', 0)}")
|
|
lines.append(f"Warnings: {summary.get('warnings', 0)}")
|
|
lines.append(f"Info: {summary.get('info', 0)}")
|
|
lines.append("")
|
|
|
|
# Detailed findings
|
|
findings = result.get("findings", [])
|
|
if findings:
|
|
lines.append("DETAILED FINDINGS")
|
|
lines.append("-" * 30)
|
|
for i, finding in enumerate(findings, 1):
|
|
severity = finding["severity"].upper()
|
|
lines.append(f"{i}. [{severity}] {finding['message']}")
|
|
lines.append(f" Rule: {finding['rule']}")
|
|
lines.append("")
|
|
else:
|
|
lines.append("No issues found. Workflow looks healthy!")
|
|
|
|
return "\n".join(lines)
|
|
|
|
|
|
def format_json_output(result: Dict[str, Any]) -> Dict[str, Any]:
|
|
"""Format results as JSON."""
|
|
return result
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# CLI Interface
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def main() -> int:
|
|
"""Main CLI entry point."""
|
|
parser = argparse.ArgumentParser(
|
|
description="Validate Jira workflow definitions for anti-patterns"
|
|
)
|
|
parser.add_argument(
|
|
"workflow_file",
|
|
help="JSON file containing workflow definition (states, transitions)",
|
|
)
|
|
parser.add_argument(
|
|
"--format",
|
|
choices=["text", "json"],
|
|
default="text",
|
|
help="Output format (default: text)",
|
|
)
|
|
|
|
args = parser.parse_args()
|
|
|
|
try:
|
|
with open(args.workflow_file, "r") as f:
|
|
data = json.load(f)
|
|
|
|
result = validate_workflow(data)
|
|
|
|
if args.format == "json":
|
|
print(json.dumps(format_json_output(result), indent=2))
|
|
else:
|
|
print(format_text_output(result))
|
|
|
|
return 0
|
|
|
|
except FileNotFoundError:
|
|
print(f"Error: File '{args.workflow_file}' not found", file=sys.stderr)
|
|
return 1
|
|
except json.JSONDecodeError as e:
|
|
print(f"Error: Invalid JSON in '{args.workflow_file}': {e}", file=sys.stderr)
|
|
return 1
|
|
except Exception as e:
|
|
print(f"Error: {e}", file=sys.stderr)
|
|
return 1
|
|
|
|
|
|
if __name__ == "__main__":
|
|
sys.exit(main())
|