pre-mortem-analystImagine the project already failed, then work backward to find why. More powerful than risk assessment because it assumes failure is certain. Use when user says "pre-mortem", "premortem", "imagine this failed", "what could go wrong", "risk analysis", "before we launch", "stress test", "what would kill this", "project risks".
Install via ClawdBot CLI:
clawdbot install artyomx33/pre-mortem-analystRisk Assessment: "What MIGHT go wrong?" → Optimism bias filters answers
Pre-Mortem: "It's 6 months later. It FAILED. Why?" → Liberates honest analysis
Research: Pre-mortems increase problem identification by 30%.
PROJECT: [Name]
FAILURE SCENARIO: "It's [date]. [Project] has completely failed."
WHY IT FAILED:
👥 PEOPLE: [Cause] - L×I: H/H | Prevent: [x] | Warning: [y]
⚙️ PROCESS: [Cause] - L×I: M/H | Prevent: [x] | Warning: [y]
💻 TECHNOLOGY: [Cause] - L×I: L/H | Prevent: [x] | Warning: [y]
🌍 EXTERNAL: [Cause] - L×I: M/M | Prevent: [x] | Warning: [y]
TOP 3 PRIORITIES:
1. [Risk] → [Specific action]
2. [Risk] → [Specific action]
3. [Risk] → [Specific action]
WARNING SIGNS TO MONITOR:
□ [Early indicator 1]
□ [Early indicator 2]
| Category | Common Causes |
|----------|---------------|
| People | Key person leaves, skill gaps, misalignment, low buy-in |
| Process | Aggressive timeline, scope creep, dependency issues |
| Tech | Doesn't scale, integration fails, security breach |
| External | Market shift, competitor move, regulation change |
Compounds with:
See references/examples.md for Artem-specific pre-mortems
Generated Mar 1, 2026
A tech startup is preparing to launch a new SaaS platform. The pre-mortem analyst helps identify potential failure points like poor user onboarding, server scalability issues, or inadequate market research before the release date.
A construction firm is planning a large-scale building project. The skill is used to foresee risks such as supply chain delays, safety incidents, or budget overruns by assuming the project has already failed.
A marketing team is launching a new advertising campaign. The pre-mortem analyst uncovers failure causes like misaligned messaging, poor audience targeting, or insufficient budget allocation to prevent wasted resources.
A hospital is integrating a new electronic health records system. The skill helps anticipate failures due to staff resistance, technical glitches, or compliance issues to ensure smooth adoption and patient safety.
An organization is organizing a major industry conference. The pre-mortem analyst identifies risks such as low attendance, logistical failures, or speaker cancellations to develop contingency plans and ensure success.
Offer pre-mortem analysis as a paid consulting service to businesses planning projects. This model involves one-on-one sessions or workshops to identify risks and develop mitigation strategies, generating revenue through hourly rates or project-based fees.
Integrate the pre-mortem analyst skill into existing project management or risk assessment software as a premium feature. This model provides automated analysis tools, with revenue from subscription tiers or per-use charges for enterprise clients.
Develop and sell training courses or certifications on pre-mortem techniques to professionals in industries like project management or product development. This model includes online modules, workshops, and certification exams for recurring revenue.
💬 Integration Tip
Combine with inversion-strategist to systematically avoid identified risks and second-order-consequences to project the impact of prevented failures for deeper analysis.
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Humanize AI-generated text to bypass detection. This humanizer rewrites ChatGPT, Claude, and GPT content to sound natural and pass AI detectors like GPTZero,...
Collaborative thinking partner for exploring complex problems through questioning
Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 24 pattern detectors, 500+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
根据用户的功能需求,完成与 VeADK 相关的功能。
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.