pf-discovery-docs v1.1

Professional client discovery document generator for consultants and agencies. Rapidly create professionally structured questionnaires (SPIN Selling), assessments (McKinsey 7S), gap analyses (Nadler-Tushman), and requirements specs (IEEE 29148) as polished DOCX files — grounded in 15 authoritative consulting frameworks.

Installation

1. Download the pf-discovery-docs.plugin file
2. Open Claude Desktop and navigate to Settings > Plugins
3. Click Install Plugin and select the downloaded .plugin file
4. The plugin will be installed and available immediately

Note: All data stays local on your machine. No external API calls or cloud storage required.

Why This Exists

Consultants spend weeks gathering discovery information using expensive tools (Content Snare $108-828/yr, Typeform $348-1,188/yr, SurveyMonkey $468-2,388/yr). This plugin generates professional discovery documents locally in minutes, as an alternative to subscription tools while maintaining quality and professionalism.

Problem

• Questionnaires are generic, not client-ready
• Assessment notes are scattered across emails and documents
• Gap analysis requires manual prioritization
• Requirements gathering is ad-hoc and inconsistent

Solution

Automated, sourced discovery documents that maintain traceability from notes to recommendations.

Quick Start

1. Initialize Workspace

discovery-setup

Creates folder structure and configuration.

2. Generate Questionnaire

discovery-questionnaire "Technology" "Assessment" "standard" "Acme Corp"

Creates industry-specific questionnaire DOCX. Share with client.

3. Generate Assessment

discovery-assessment "Acme Corp" "inbound/discovery-notes.txt"

Analyzes client notes, extracts findings with source attribution.

4. Generate Gap Analysis

discovery-gap-analysis "Acme Corp" "Cloud-based CRM with automated workflows"

Compares current state to target state with priority matrix.

5. Generate Requirements

discovery-requirements "CRM Implementation" "Salesforce deployment with ERP integration"

Structured requirements spec with MUST/SHOULD/COULD priorities.

Or All at Once

discovery-full-cycle "Acme Corp" "Technology"

Commands

Command	Purpose
discovery-setup	Initialize workspace
discovery-questionnaire [industry] [type] [depth] [client]	Generate questionnaire
discovery-assessment [client] [notes-file]	Analyze notes, extract findings
discovery-gap-analysis [client] [target-state]	Compare current vs target
discovery-requirements [project-type] [scope]	Generate requirements spec
discovery-full-cycle [client] [industry]	Run all steps sequentially
discovery-kb [framework-name]	Display consulting knowledge base
discovery-status [client]	Show workspace status

How It Works

Architecture: Hub-and-Spoke

• Hub: discovery-setup initializes shared workspace
• Spoke 1: discovery-questionnaire (industry-specific)
• Spoke 2: discovery-assessment (sourced findings)
• Spoke 3: discovery-gap-analysis (prioritized gaps)
• Spoke 4: discovery-requirements (structured specs)

Sourcing & Traceability

Every finding includes:

• source_line: Line number in input
• source_quote: Exact phrase from input (≤80 chars)
• finding_id: Reference ID (PAIN-001, TECH-001, etc.)

Gap analysis references assessment findings — no hallucination.

Alternatives

Tool	Cost/Year	Limitations
Content Snare	$108-828	Subscription, limited customization
Typeform	$348-1,188	Generic forms, no gap analysis
SurveyMonkey	$468-2,388	Survey-focused, no assessment
Manual (Word)	0	Time-consuming, inconsistent
pf-discovery-docs	0	Automated, professional, sourced

Differentiators

• Local generation: No cloud dependency, no vendor lock-in
• Sourced findings: Every claim references discovery input
• Industry-aware: Customizable questions per industry
• Gap prioritization: 2x2 matrix (Impact vs Effort)
• Structured output: Professional DOCX files ready to share
• Extensible: Easy to customize templates and add new industries

AI-Powered Features

1. SPIN-Structured Questionnaires: Generates questionnaires using SPIN Selling framework (Rackham, 1988) with Situation/Problem/Implication/Need-Payoff question tagging and distribution tracking
2. McKinsey 7S Assessment: Categorizes findings across all 7 organizational dimensions (Peters & Waterman, 1982) with explicit "not assessed" flagging for uncovered areas
3. TOGAF Architecture Classification: Organizes technology stack by TOGAF ADM layers — Business Applications, Data & Analytics, Infrastructure, Collaboration, DevOps (The Open Group, 2022)
4. CMMI Maturity Estimation: Estimates organizational process maturity per CMMI v2.0 (CMMI Institute, 2018) with evidence-based rationale
5. ISO 31000 Severity Calibration: Rates pain point severity using likelihood × impact per ISO 31000:2018 risk management framework
6. Nadler-Tushman Gap Categorization: Classifies gaps across Work, People, Formal Organization, Informal Organization per Congruence Model (1980)
7. Burke-Litwin Change Guard: Prevents misclassifying Transformational changes as Quick Wins per Burke-Litwin change model (1992)
8. IEEE 29148 Requirements Structure: Generates requirements specs per ISO/IEC/IEEE 29148:2018 with mandatory sections (Purpose, Scope, Qualification)
9. BABOK v3 Classification: Classifies requirements as Business, Functional, Non-functional, and Transition per IIBA BABOK v3 §6 (2015)
10. MoSCoW Distribution Validation: Validates priority distribution per Clegg & Barker (1994) — flags inflated >80% Must allocations
11. Kano Model Categories: Tags requirements as Must-Be, One-Dimensional, or Attractive per Kano (1984) to identify delighters vs. table stakes
12. INVEST Quality Scoring: Checks requirement quality against Independent/Negotiable/Valuable/Estimable/Small/Testable criteria (Wake, 2003)
13. Centralized Knowledge Base: 15 authoritative frameworks with source-level citations in a single reference skill — all other skills draw from this KB
14. Anti-Hallucination Sourcing: Every assessment finding includes traceable source (line number, quote) — no invented statistics per 6 explicit anti-hallucination rules
15. Stakeholder Identification: Identifies decision-makers per Mitchell, Agle & Wood (1997) Power/Legitimacy/Urgency stakeholder theory

Feature Comparison

Feature	Content Snare	Typeform	SurveyMonkey	pf-discovery-docs
Questionnaire generation	Yes	Yes	Yes	Yes
SPIN Selling question structure	No	No	No	Yes
Assessment analysis	No	No	No	Yes
McKinsey 7S categorization	No	No	No	Yes
TOGAF architecture classification	No	No	No	Yes
CMMI maturity estimation	No	No	No	Yes
Gap analysis	No	No	No	Yes
Nadler-Tushman gap categorization	No	No	No	Yes
Burke-Litwin change difficulty	No	No	No	Yes
Requirements template	No	No	No	Yes
IEEE 29148 requirements structure	No	No	No	Yes
BABOK v3 requirement classification	No	No	No	Yes
MoSCoW distribution validation	No	No	No	Yes
Kano Model categories	No	No	No	Yes
Priority matrix	No	No	No	Yes
ISO 31000 severity calibration	No	No	No	Yes
Centralized knowledge base	No	No	No	Yes
Anti-hallucination sourcing	No	Limited	No	Yes
Local generation	No	No	No	Yes
DOCX output	Yes	PDF only	PDF only	Yes
No recurring cost	No	No	No	Yes
Self-hosted	No	No	No	Yes

Limitations

• Manual review required: AI-extracted findings should be verified
• Quality depends on input: Vague notes yield vague findings
• No team collaboration UI: Documents shared via email/Drive
• Single-user basis: Not multi-user SaaS platform
• Python-docx constraints: Styling limited vs. Word UI
• Single-language: English only (current version)

Context Guide

For Consultants

1. Run discovery-setup once at project start
2. Generate questionnaire and share with client
3. Collect responses in inbound/discovery-notes.txt
4. Generate assessment → gap analysis → requirements automatically
5. Archive when complete: documents move to archive/

For Agencies

1. Customize branding in .discovery/config.json per client
2. Use discovery-full-cycle for batch processing
3. Store completed assessments for future reference
4. Reuse gap analysis templates for similar industries

For Project Managers

• Use discovery-status to track engagement progress
• Review checkpoints in .discovery/project.json
• Verify all findings before sharing with client

Estimated Cost per Use

Disclaimer: Token estimates are approximate and based on typical usage patterns measured from skill prompt sizes. Actual costs vary with input data size, conversation length, and complexity. Estimates use Claude Sonnet 4.6 pricing ($3/1M input, $15/1M output). Cowork and Claude Desktop subscription users (Pro/Max/Team) are not charged per-token — these estimates apply only to direct Anthropic API usage. Running stages individually in fresh sessions uses fewer input tokens than running the full pipeline sequentially, because pipeline mode accumulates conversation history across stages.

Per skill (run individually in a fresh session):

Stage	Skill Prompt	User Input	Total Input	Output	Est. Cost
discovery-questionnaire	~5.1K	~800	~9.0K	~5.1K	~$0.10
discovery-gap-analysis	~5.3K	~800	~9.1K	~6.0K	~$0.12
discovery-kb	~6.3K	~800	~9.9K	~6.0K	~$0.12
discovery-requirements	~7.1K	~800	~10.9K	~6.0K	~$0.12
discovery-assessment	~6.1K	~800	~10.1K	~6.0K	~$0.12
Standalone total			~49.0K	~29.1K	~$0.58

Full pipeline (all stages in one session — context accumulates):

Stage	Base Input	+ History	Total Input	Output	Est. Cost
discovery-questionnaire	~9.6K	0	~9.6K	~5.1K	~$0.11
discovery-gap-analysis	~9.8K	~5.9K	~15.7K	~6.0K	~$0.14
discovery-kb	~10.8K	~12.7K	~23.5K	~6.0K	~$0.16
discovery-requirements	~11.6K	~19.5K	~31.1K	~6.0K	~$0.18
discovery-assessment	~10.7K	~26.3K	~37.0K	~6.0K	~$0.20
Pipeline total			~116.9K	~29.1K	~$0.79

Running the full pipeline once typically costs $0.55–$1.02 in API tokens (Claude Sonnet 4.6).

Requirements

• Python 3.7+ (pre-installed)
• python-docx (auto-installed on first run)
• 50 MB disk space (for documents and logs)
• Read/write access to workspace directory

Important Disclaimers

• AI-Generated Content: This plugin uses AI (LLM) technology which can produce inaccurate or incomplete outputs. All content should be treated as a starting point and reviewed for accuracy before use.
• Not Professional Advice: Outputs do not constitute legal, financial, tax, medical, or other professional advice. Consult qualified professionals before making decisions based on generated content.
• No Compliance Guarantee: References to industry standards, regulations, or guidelines are for informational purposes only. This plugin does not guarantee compliance with any law or regulation. Users are responsible for verifying all outputs meet their specific regulatory requirements.
• No Endorsement or Affiliation: Mention of third-party products, standards, or organizations does not imply endorsement, partnership, or certification by those entities.
• Not Legal Advice: This plugin does not provide legal services or legal advice. All legal documents and analysis should be reviewed by a licensed attorney before use.