CV Boutique Agency — Claude Code Skill

If you use or adapt this project, a credit or link back to this repository is appreciated — see Citation / credit.

A top-tier boutique resume agency skill for Claude Code. Acts as a panel of eight expert reviewers — AI veteran, HR specialist, founder, business operator, devil's advocate, creative reframer, QC lead, and hallucination detector — to build, critique, rewrite, and quality-control resumes until they reach 8.5+ quality with zero hallucinated claims. Final output includes a send-ready .docx.

What this skill does

Core capability

The skill orchestrates a virtual agency panel that interviews you, drafts your resume section by section, challenges every claim, scores the result using a weighted multi-expert model, and iterates until the resume passes the stop conditions (overall score ≥ 8.5, no critical blocker flags, user acceptance).

Three operating modes

Mode 1 — Build from scratch Starts with a structured intake (language → target industry → role/seniority → geography/company stage), builds the expert panel, then works through your resume section by section: header, summary, achievements, experience, education, skills. Each section is drafted, QC-reviewed, scored, and refined before moving on.

Mode 2 — Uploaded resume critique Paste or upload your existing resume. The skill detects it, asks only for missing targeting context, then delivers a full executive verdict: strengths, weaknesses, per-section scores, critical blocker flags, and an exact fix list. You then choose to rewrite, rebuild, or tailor.

Mode 3 — Fast mode Ask only the minimum blocking questions, run the full agency process behind the scenes, enforce all QA and hallucination controls, and deliver the strongest possible result with minimal back-and-forth.

Expert panel

Mandatory (always active):

AI veteran
HR / recruiter specialist
Founder / entrepreneur
Business leader / operator
Devil's advocate
Brainstorm / creative reframer
Quality-control lead
Hallucination detector

Context-dependent additions (spawned by the CEO as context reveals the need):

Domain expert + industry-specific reviewer (when industry is provided)
Language / localization expert (when language ≠ English)
ATS specialist (corporate / large org targets)
Executive branding expert (director+ / C-suite / partner roles)

When Claude Code agent teams are enabled, each of these experts runs as a real independent Claude instance — own context window, own task, direct inter-expert messaging. See Agent teams architecture below.

Scoring model

Each expert scores independently. A weighted overall score is computed. The skill also maintains internal per-section scores and tracks critical blocker flags. It stops only when all three stop conditions are met: score ≥ 8.5, zero blockers, user acceptance.

Score range	Meaning
0 – 3	Weak / non-competitive
4 – 6	Usable but weak
7 – 8.4	Strong with clear issues
8.5 – 8.9	Send-ready strong
9.0 – 9.4	Must-call quality
9.5+	Exceptional (rare)

Hard rules

No hallucinated claims — ever
No unsupported percentages or metrics
No fake or inflated seniority
No generic self-praise without evidence
No sugarcoating — if something is weak, the panel will say so
Memory (workspace/memory.json) and progress (workspace/progress.json) are updated at every stage

Final output bundle

Final resume (formatted text)
Panel report (per-expert verdicts)
Scorecard (per-section + weighted overall)
Rewrite / action plan
Downloadable .docx

Optional extras: tailored variants, LinkedIn summary, cover letter starter, interview talking points

Fun epilogue: once your resume is delivered, the agency offers to channel a famous figure from your industry (or a historical wildcard) for a 3–4 sentence in-character reaction to your resume — Elon Musk, Warren Buffett, Marie Curie, Sun Tzu, and more. Purely for fun; zero effect on the resume or scores.

Repository layout

CV_Boutique_Agency/
  CLAUDE.md                    # Wires skill to this project
  README.md                    # This file
  requirements.txt             # Python dependency (python-docx)
  .gitignore
  .claude-plugin/              # Marketplace catalog (plugin distribution)
    marketplace.json
  boutique-resume-agency/      # Plugin folder
    .claude-plugin/
      plugin.json              # Plugin manifest
    skills/
      boutique-resume-agency/
        SKILL.md               # Main skill file with YAML frontmatter
    scripts/
      resume_agency_helpers.py # Panel building, weighted scoring, length checks
      memory_manager.py        # Load/save memory.json and progress.json
      docx_export.py           # DOCX export via python-docx
      _file_utils.py           # Shared atomic JSON write utility
    tests/
      test_resume_agency_helpers.py # 204 pytest tests across 4 files, 100% coverage
      test_e2e.py
      test_docx_export.py
      test_memory_manager.py
    references/
      templates.md             # Intake + critique + output templates
      scoring_rubric.md        # Score scale, blocker flags, pass criteria
      memory_progress_spec.md  # JSON schemas for memory and progress files
      example_flows.md         # Step-by-step example flows for each path
  workspace/
    memory.json                # Persistent session memory
    progress.json              # Stage tracking and scores
    outputs/                   # Generated .docx files land here

Installation

Choose the setup that fits you:

Option	Who it's for	Time
Plugin (one command)	Claude Code users — quickest start	30 sec
Local clone	Claude Code users — want full control	5 min
Claude.ai Project	No Claude Code — using Claude desktop or browser app	5 min

Install as a plugin (one command)

If this repo is public on GitHub, anyone can install the skill directly from Claude Code:

/plugin marketplace add stevesolun/CV_Boutique_Agency
/plugin install boutique-resume-agency@cv-boutique-agency

That's it — no cloning, no pip install needed to get the skill. Python (python -m pip install python-docx) is only needed if you want DOCX export.

Install locally (clone the repo)

Prerequisites

Claude Code installed and running
Python 3.9+ (only needed for DOCX export)

Step 1 — Clone or download the repo

git clone https://github.com/stevesolun/CV_Boutique_Agency
cd CV_Boutique_Agency

Or download and extract the ZIP, then open the folder.

Step 2 — Install the Python dependency

The DOCX export function requires python-docx. Install it once:

python -m pip install python-docx

Why python -m pip and not pip? On machines with multiple Python versions, bare pip may target a different interpreter than python. Using python -m pip ensures both commands hit the same installation.

To verify:

python -c "from docx import Document; print('python-docx OK')"

Step 3 — Open the project in Claude Code

Open the CV_Boutique_Agency folder in Claude Code. Claude Code automatically reads CLAUDE.md on project open and activates the boutique resume agency skill.

You do not need to manually load any files. The skill is ready to use immediately.

Step 4 — Verify workspace files

The workspace/ folder ships with initialized memory.json and progress.json. Confirm they exist:

cat workspace/memory.json
cat workspace/progress.json

If either file is missing, regenerate defaults:

python -c "
import sys, json, pathlib
sys.path.insert(0, 'boutique-resume-agency/scripts')
from memory_manager import DEFAULT_MEMORY, DEFAULT_PROGRESS
pathlib.Path('workspace/memory.json').write_text(json.dumps(DEFAULT_MEMORY, indent=2))
pathlib.Path('workspace/progress.json').write_text(json.dumps(DEFAULT_PROGRESS, indent=2))
print('workspace files restored')
"

Use in Claude.ai (no Claude Code needed)

No terminal, no install. The full expert panel, scoring model, intake flows, and resume length research all work inside a Claude Project on claude.ai — on any device (Windows, Mac, Linux, browser).

What works in Claude.ai

Feature	Works?	Notes
Expert panel (all 8 experts)	✅	Full panel runs in conversation
Build from scratch (Path A)	✅	Section by section
Upload / critique resume (Path B)	✅	Paste your resume into the chat
Scoring model	✅	Per-expert + weighted overall
Hallucination detection	✅	All hard blocks enforced
Resume length research	✅	Claude.ai can search the web
Fast mode	✅	Say `fast mode` as normal
Memory / progress persistence	⚠️	State lives in the conversation only — not persisted across sessions
DOCX export (auto)	⚠️	Requires manual script run (see below)
Python script execution (auto)	❌	No file system access

Setup — Claude Project (5 minutes)

Step 1 — Create a new Project

Go to claude.ai → Projects → New Project. Give it a name like "CV Boutique Agency".

Step 2 — Set the skill as Project Instructions

Open the Project → Instructions → paste the full contents of boutique-resume-agency/skills/boutique-resume-agency/SKILL.md into the instructions field.

The agency will activate automatically for every conversation in this Project.

Step 3 — Upload the reference files

Upload these files to the Project's knowledge base (drag and drop):

boutique-resume-agency/references/templates.md
boutique-resume-agency/references/scoring_rubric.md
boutique-resume-agency/references/example_flows.md
boutique-resume-agency/references/memory_progress_spec.md

Step 4 — Start a conversation

Use the same trigger phrases as Claude Code. The agency activates immediately.

DOCX export in Claude.ai

Claude.ai cannot execute Python directly, but you have two options:

Option A — Copy-paste into Word / Google Docs

When the resume reaches 8.5+, ask:

Format the final resume for copy-paste into Microsoft Word.

Claude will produce clean, structured text you can paste directly.

Option B — Run the export script manually

Ask Claude to produce the resume_data dict, then run it yourself:

Give me the resume_data dict for docx_export.py.

Then locally:

cd CV_Boutique_Agency
python -c "
import sys; sys.path.insert(0, 'boutique-resume-agency/scripts')
from docx_export import export_resume_to_docx
resume_data = { ... }  # paste dict from Claude
export_resume_to_docx(resume_data, 'workspace/outputs/my_resume.docx')
"

Session memory in Claude.ai

Memory doesn't auto-persist between conversations. To continue a session:

At the end of a session, ask: Give me the current memory.json and progress.json state.
Claude will output the JSON.
At the start of your next session, paste it back: Here's my previous session state: [paste JSON]

Usage

Mode reference

Mode	How to activate	What happens
Tier 1 — Simulation (default)	Just start a session — no config needed	CEO simulates all 8+ experts in one context window. Works on Claude.ai, Claude Code, any subscription tier.
Tier 2 — Agent teams (experimental)	Enable `CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1` in settings.json + Claude Code v2.1.32+	Every expert runs as a real independent Claude instance with its own context. See Agent teams architecture.
Fast mode	Say `fast mode` or type `/fast` in the conversation	Skips non-critical intake questions. Full agency logic runs behind the scenes. All QA and hallucination controls still enforced.
Interactive mode (default)	No phrase needed, or say `interactive mode`	One section at a time, full back-and-forth with the panel.
Build from scratch	`build my resume`	Full intake → section-by-section build → score → export
Critique / rewrite	Paste resume + `critique my resume`	Executive verdict, per-section scores, fix list
Tailor to JD	`tailor my resume for this JD:` + paste JD	Gap analysis, fit score, tailored version

Toggling fast mode

Say fast mode or type /fast at any point in the session (or prefix the session opener: fast mode. build my resume). These are skill trigger phrases — say them in the conversation, not as top-level CLI commands.

Fast mode skips geography, company stage, and other optional intake questions. The agency asks only the minimum blocking questions (language, path, industry/role) and then works autonomously.

To return to interactive mode, say interactive mode or standard mode.

Toggling Tier 2 (agent teams)

See Tier 2 setup in the Agent teams section. To disable, remove CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS from settings.json — the agency falls back to Tier 1 simulation automatically with no change to the user experience.

Start a session

Tell Claude Code (or Claude.ai with a Project) any of the following:

Build my resume from scratch.

I have my current resume here. Critique it.

Fast mode. Make this resume must-call quality.

Tailor my resume for this job description: [paste JD]

Push this resume to 9+ if realistically possible.

Recommended trigger phrases

Goal	Phrase
Build from scratch	`build my resume`, `resume from scratch`
Critique existing	`critique my resume`, `resume critique`
Full rewrite	`rewrite my resume`
Role-specific tailoring	`tailor my resume`
Minimal questions	`fast mode resume`
Activate explicitly	`boutique resume agency`

Export to DOCX

Once the resume reaches 8.5+ and you accept it, Claude Code will call docx_export.py and save the file to workspace/outputs/. You can also request it explicitly:

Export the final resume to DOCX.

Troubleshooting

DOCX export fails with ModuleNotFoundError python-docx is not installed. Run python -m pip install python-docx and retry. Use python -m pip (not bare pip) to ensure the package is installed for the same Python interpreter Claude Code is using.

Skill not activating Confirm you opened the CV_Boutique_Agency folder (not a parent folder) in Claude Code so that CLAUDE.md is loaded.

Score stuck below 8.5 after multiple iterations There are unresolved critical blocker flags. Review boutique-resume-agency/references/scoring_rubric.md for the full blocker flag list. Address each flag explicitly before re-scoring.

Memory or progress file corrupted Delete the affected file and let the skill regenerate it, or run the restore script in Step 4 above.

Agent teams architecture (experimental)

The boutique resume agency uses a two-tier execution model. The expert panel, scoring, hallucination detection, and context-dependent expert additions are identical in both tiers — only the execution model differs.

Two-tier overview

	Tier 1 — Simulation (default)	Tier 2 — Agent teams (experimental)
Works on	Claude.ai, Claude Code, any tier — zero config	Claude Code v2.1.32+ with `CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1`
Execution model	CEO simulates all experts in one context window	Every expert is a real independent Claude instance
Context-dependent experts	✅ CEO adds them via simulation as context reveals the need	✅ CEO spawns real subagents on-the-fly with full context
Scoring / QC / hallucination detection	✅ Identical logic	✅ Identical logic
Expert-to-expert messaging	Simulated by CEO	Real direct inter-expert messages
Token cost	Single context window	Scales with active experts (8–13 instances)
Session announcement	"Running in agency simulation mode…"	No announcement — normal operation

Both tiers share the same stop conditions, scoring weights, blocker flags, and export flow.

Tier 2 setup (Claude Code)

Step 1 — Verify Claude Code version

claude --version   # must be v2.1.32+

Step 2 — Enable agent teams

// settings.json
{
  "env": {
    "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1"
  }
}

Step 3 — Start a session as normal. The CEO runs the full Tier 2 flow automatically — no special trigger phrase needed.

The "experimental" label is honest: the Claude Code agent teams API itself is experimental. The skill's architecture and protocols are production-ready.

How Tier 2 works

Session start: CEO spawns all 8 mandatory core experts. Each expert receives a full spawn prompt with persona, scope, input contract (session context + task object), and required JSON output format.

Wave execution per review cycle:

Wave 1 (parallel): AI Veteran, HR Specialist, Founder, Business Operator, Domain Expert (if active), ATS Specialist (if active)
Wave 2 (after Wave 1): Devil's Advocate, Creative Reframer
Wave 3 (after Wave 2): QC Lead, Hallucination Detector

Context-dependent experts: When intake reveals a specific industry, senior role, non-English language, or high-norm sector, the CEO generates a full tailored spawn prompt and spawns the specialist as a real subagent at that moment.

Synthesis: CEO reads all expert return contracts, runs weighted_score(), promotes any HARD_BLOCK: flag (Hallucination Detector) to a confirmed blocker regardless of other scores, and presents the panel verdict.

Error / timeout: Expert timeout = 90 seconds. On timeout, CEO marks status error, redistributes that expert's weight across remaining experts via normalization, and continues. Hallucination Detector failure blocks export entirely until resolved.

Full production spec

Complete spawn prompts (one per expert, ~15 lines each), input/return contract JSON schemas, and error-handling protocol are defined in SKILL.md under "Agent teams architecture".

Windows / VS Code note

In-process mode (default) works on Windows and in VS Code's integrated terminal. Split-pane mode requires tmux or iTerm2 and is not available in VS Code. Use Shift+Down to cycle between active expert sessions.

Score targets quick reference

Target	Score	Meaning
Minimum to stop	8.5+	Send-ready
Strong target	9.0+	Must-call quality
Exceptional	9.5+	Rare — only when evidence fully supports it

Citation / credit

This project is released under the MIT License. You are free to use, adapt, and redistribute it. If you use or build on this work, a credit or link back is appreciated but not legally required.

Suggested citation format:

Solun, S. (2026). CV Boutique Agency — Claude Code Skill [Software].
GitHub. https://github.com/stevesolun/CV_Boutique_Agency

BibTeX:

@software{solun2026cvboutique,
  author    = {Solun, Steve},
  title     = {{CV Boutique Agency} — Claude Code Skill},
  year      = {2026},
  publisher = {GitHub},
  url       = {https://github.com/stevesolun/CV_Boutique_Agency}
}

Name		Name	Last commit message	Last commit date
Latest commit History 30 Commits
.claude-plugin		.claude-plugin
boutique-resume-agency		boutique-resume-agency
workspace		workspace
.gitignore		.gitignore
CLAUDE.md		CLAUDE.md
LICENSE		LICENSE
README.md		README.md
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt

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CV Boutique Agency — Claude Code Skill

What this skill does

Core capability

Three operating modes

Expert panel

Scoring model

Hard rules

Final output bundle

Repository layout

Installation

Install as a plugin (one command)

Install locally (clone the repo)

Prerequisites

Step 1 — Clone or download the repo

Step 2 — Install the Python dependency

Step 3 — Open the project in Claude Code

Step 4 — Verify workspace files

Use in Claude.ai (no Claude Code needed)

What works in Claude.ai

Setup — Claude Project (5 minutes)

DOCX export in Claude.ai

Session memory in Claude.ai

Usage

Mode reference

Toggling fast mode

Toggling Tier 2 (agent teams)

Start a session

Recommended trigger phrases

Export to DOCX

Troubleshooting

Agent teams architecture (experimental)

Two-tier overview

Tier 2 setup (Claude Code)

How Tier 2 works

Full production spec

Windows / VS Code note

Score targets quick reference

Citation / credit

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