Dev (#305)

* 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>

c-level-advisor/cto-advisor/scripts/team_scaling_calculator.py

@@ -323,8 +323,30 @@ class TeamScalingCalculator:
                 'designer': 120000,
                 'data_engineer': 140000
             },
-            'EU': {k: v * 0.8 for k, v in salary_bands.get('US', {}).items()},
-            'APAC': {k: v * 0.6 for k, v in salary_bands.get('US', {}).items()}
+            'EU': {
+                'engineering_manager': 160000,
+                'tech_lead': 144000,
+                'senior_engineer': 128000,
+                'mid_engineer': 96000,
+                'junior_engineer': 68000,
+                'devops': 120000,
+                'qa': 80000,
+                'product_manager': 120000,
+                'designer': 96000,
+                'data_engineer': 112000
+            },
+            'APAC': {
+                'engineering_manager': 120000,
+                'tech_lead': 108000,
+                'senior_engineer': 96000,
+                'mid_engineer': 72000,
+                'junior_engineer': 51000,
+                'devops': 90000,
+                'qa': 60000,
+                'product_manager': 90000,
+                'designer': 72000,
+                'data_engineer': 84000
+            }
         }
         
         location_salaries = salary_bands.get(location, salary_bands['US'])
@@ -493,24 +515,48 @@ def calculate_team_scaling(current_state: Dict, growth_targets: Dict) -> str:
     return '\n'.join(output)
 
 if __name__ == "__main__":
-    # Example usage
-    example_current = {
-        'headcount': 25,
-        'velocity': 450,
-        'roles': {
-            'engineering_manager': 2,
-            'tech_lead': 3,
-            'senior_engineer': 8,
-            'mid_engineer': 10,
-            'junior_engineer': 2
-        },
-        'attrition_rate': 12,
-        'location': 'US'
-    }
-    
-    example_targets = {
-        'target_headcount': 75,
-        'timeline_quarters': 4
-    }
-    
-    print(calculate_team_scaling(example_current, example_targets))
+    import argparse
+
+    parser = argparse.ArgumentParser(
+        description="Engineering Team Scaling Calculator - Optimize team growth and structure"
+    )
+    parser.add_argument(
+        "input_file", nargs="?", default=None,
+        help="JSON file with current_state and growth_targets (default: run with sample data)"
+    )
+    parser.add_argument(
+        "--json", action="store_true",
+        help="Output raw JSON instead of formatted report"
+    )
+    args = parser.parse_args()
+
+    if args.input_file:
+        with open(args.input_file) as f:
+            data = json.load(f)
+        current_state = data["current_state"]
+        growth_targets = data["growth_targets"]
+    else:
+        current_state = {
+            'headcount': 25,
+            'velocity': 450,
+            'roles': {
+                'engineering_manager': 2,
+                'tech_lead': 3,
+                'senior_engineer': 8,
+                'mid_engineer': 10,
+                'junior_engineer': 2
+            },
+            'attrition_rate': 12,
+            'location': 'US'
+        }
+        growth_targets = {
+            'target_headcount': 75,
+            'timeline_quarters': 4
+        }
+
+    if args.json:
+        calculator = TeamScalingCalculator()
+        results = calculator.calculate_scaling_plan(current_state, growth_targets)
+        print(json.dumps(results, indent=2))
+    else:
+        print(calculate_team_scaling(current_state, growth_targets))