Monitor CI
nrwl/nx
Monitor Nx Cloud CI pipeline and handle self-healing fixes. An agent skill from nrwl/nx.
Imagine the project has already shipped and failed catastrophically — work backwards from the failure to identify the most likely causes BEFORE building.
Install Pre Mortem
$ npx skills add avelikiy/great_cto --skill pre-mortem -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install avelikiy/great_cto pre-mortem --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/pre-mortem .claude/skills/pre-mortem && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "pre-mortem" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/pre-mortem into .claude/skills/pre-mortem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pre-mortem", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/avelikiy/great_cto/tree/main/skills/pre-mortemType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add avelikiy/great_cto --skill pre-mortem -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install avelikiy/great_cto pre-mortem --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/pre-mortem .agents/skills/pre-mortem && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "pre-mortem" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/pre-mortem into .agents/skills/pre-mortem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pre-mortem", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add avelikiy/great_cto --skill pre-mortem -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install avelikiy/great_cto pre-mortem --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/pre-mortem .cursor/skills/pre-mortem && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "pre-mortem" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/pre-mortem into .cursor/skills/pre-mortem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pre-mortem", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/avelikiy/great_cto.git --path skills/pre-mortem--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add avelikiy/great_cto --skill pre-mortem -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install avelikiy/great_cto pre-mortem --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/pre-mortem .gemini/skills/pre-mortem && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "pre-mortem" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/pre-mortem into .gemini/skills/pre-mortem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pre-mortem", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install avelikiy/great_cto pre-mortemInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add avelikiy/great_cto --skill pre-mortem -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/pre-mortem .github/skills/pre-mortem && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "pre-mortem" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/pre-mortem into .github/skills/pre-mortem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pre-mortem", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add avelikiy/great_cto --skill pre-mortem -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install avelikiy/great_cto pre-mortem --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/avelikiy/great_cto.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/pre-mortem .opencode/skills/pre-mortem && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "pre-mortem" agent skill from https://github.com/avelikiy/great_cto/tree/main/skills/pre-mortem into .opencode/skills/pre-mortem/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pre-mortem", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
pre-mortem- GitHub stars
- 103
- Token cost
- ~1.6k tokens
- SKILL.md length
- 661 words
- Files
- 1
- Skills in repo
- 27
- Repo updated
- First seen
- Licence
- MIT
At a glance
Imagine the project has already shipped and failed catastrophically — work backwards from the failure to identify the most likely causes BEFORE building.
- Works in 5 steps: Imagine you're 6 months in the future → Write the post-mortem newspaper headline → List every individual reason this exact… → …
- DevOps & Cloud work in your project
- SKILL.md covers The 5-step pre-mortem, Template — add to PLAN-*.md, Common failure modes by… and Anti-patterns in pre-mortems, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Pre Mortem is an agent skill from avelikiy/great_cto. Imagine the project has already shipped and failed catastrophically — work backwards from the failure to identify the most likely causes BEFORE building. Forces concrete risk identification, not vague "what could go wrong" lists.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud. The repository describes itself as: You already have the agent. This is everything around it. greatcto runs Claude Code as a pipeline of 70 specialist agents — an independent model checks each stage before the next… The licence is MIT.
When your agent uses it
- DevOps & Cloud work in your project
Example prompts
- “what could go wrong”
- “/pre-mortem”
Requirements
- Pre-approved tools (allowed-tools): Read, Write
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 5d6e760. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWrite
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Pre Mortem loads about 1.6k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 661 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from avelikiy/great_cto at commit 5d6e760, republished under its MIT licence (© avelikiy). 661 words, ~1,645 tokens.
Download SKILL.mdSave it as
.claude/skills/pre-mortem/SKILL.md (or your agent's skills folder).- name
- pre-mortem
- description
- Imagine the project has already shipped and failed catastrophically — work backwards from the failure to identify the most likely causes BEFORE building. Forces concrete risk identification, not vague "what could go wrong" lists.
- allowed-tools
- Read, Write
- when_to_use
- Apply BEFORE implementation begins: - architect, after writing ARCH but before gate:plan - pm, while breaking work into tasks (Pre-mortem section in…
- effort
- medium
- paths
- docs/plans/**, docs/architecture/**, docs/threat-models/**
Pre-mortem — fail-it-before-you-build-it
A retrospective for a project that hasn't happened yet. Surfaces real risks that "list every risk" prompts miss.
Originated in Gary Klein's research at MIT Sloan, now standard at AWS and other ops-mature orgs.
The 5-step pre-mortem
Step 1. Imagine you're 6 months in the future
The project shipped. It is a clear, public failure. There's a Reddit thread about it. The CEO is asking what went wrong.
Step 2. Write the post-mortem newspaper headline
One sentence. Concrete. Specific. Examples:
- ❌ Bad: "We had some quality issues."
- ✅ Good: "On 2026-09-12, the Stripe webhook handler deduplicated by raw body hash, so 30K customers were double-charged after Stripe retried delivery during a network blip."
The headline forces you to name the failure mode SPECIFICALLY.
Step 3. List every individual reason this exact failure happened
Brainstorm 10-15 reasons. Be specific. Each item should reference:
- A real component / file
- A real failure mode (race condition, schema mismatch, expired credential)
- A real human factor (oncall didn't see alert, runbook was outdated)
Reject hand-waves like "testing was insufficient." Replace with "we didn't write a property-based test for the dedup-key collision case."
Step 4. Rank by likelihood × severity
For each cause, score:
- Likelihood: 1-5 (1=once-in-a-decade, 5=monthly)
- Severity: 1-5 (1=cosmetic, 5=data loss / regulatory breach)
- Risk score: likelihood × severity
Top 3 by risk score → these are your highest-priority mitigations.
Step 4b. Classify risks — Tigers / Paper Tigers / Elephants
After scoring, classify each risk into one of three types:
🐯 Tigers — Real problems you personally believe could derail the project
- Based on evidence, past experience, or clear logic
- Should keep you awake at night
- Require concrete action
- Classify each Tiger by urgency:
- Launch-Blocking: Must be resolved before shipping (broken core feature, regulatory blocker, data integrity risk)
- Fast-Follow: Must be resolved within 30 days post-launch (performance issues, secondary features)
- Track: Monitor post-launch, fix if it becomes an issue (edge cases, nice-to-haves)
📄 Paper Tigers — Concerns others might raise that you don't believe are real risks
- Valid-sounding on the surface but unlikely or overblown
- Not worth significant resource investment
- Worth documenting to align stakeholders and avoid repeated debates
- For each: explain WHY you don't believe it's a real risk
🐘 Elephants — Things the team knows about but isn't discussing openly
- Uncomfortable concerns: technical debt, team tension, unrealistic timeline, design that nobody likes
- Uncertain — you're not sure if it's a problem, but nobody is investigating
- Deserve explicit surfacing before launch — silent elephants become Tigers post-launch
Show full SKILL.md (262 more words)Show less
Step 5. For each top-3 cause, write a guardrail in the plan
Each guardrail is a concrete change to the plan:
- A test that would have caught it
- A circuit breaker / feature flag
- A runbook entry
- A monitoring alert with specific SLO
If a top-3 cause CANNOT be mitigated within the time/budget, escalate to the user: "This plan accepts the risk of X with no mitigation."
Template — add to PLAN-*.md
## Pre-mortem
Six months from now, this project failed. Headline:
> <one-sentence failure headline>
### Top reasons (likelihood × severity)
| Cause | L | S | Risk | Mitigation in plan |
|---|---|---|---|---|
| <specific cause> | 4 | 5 | 20 | <Task #N: write idempotency test> |
| ... | | | | |
### 🐯 Tigers (real risks — require action)
| Tiger | Classification | Mitigation | Owner | Due |
|-------|---------------|-----------|-------|-----|
| <risk> | Launch-Blocking | <concrete action> | <team/person> | <date> |
| <risk> | Fast-Follow | <concrete action> | <team/person> | <date> |
| <risk> | Track | <monitoring approach> | <owner> | post-launch |
### 📄 Paper Tigers (overblown — document to align stakeholders)
- **<concern>**: Not a real risk because <reason>. If <condition> changes, revisit.
### 🐘 Elephants (unspoken — needs open discussion)
- **<concern>**: Nobody is talking about this. Suggested conversation: "<how to raise it>".
### Accepted risks (no mitigation)
- <risk> — accepted because <budget/scope reason>. Owner: <name>.Common failure modes by archetype
Quick start — most-common pre-mortem causes per archetype:
| Archetype | Common failure |
|---|---|
| fintech / commerce | Idempotency-key collision; double-charge during retry storm |
| healthcare | PHI leak via debug log; BAA not signed with vendor |
| web3 | Oracle staleness; flash-loan exploit on bonding curve |
| mlops | Training/serving skew; model drift undetected |
| iot-embedded | OTA bricks devices in a region with no recovery path |
| data-platform | Late-arriving data overwrites correct values |
| ai-system / agent-product | Prompt injection exfiltrates other users' data |
| enterprise-saas | Cross-tenant data leak via RLS gap |
| cli-tool | Destructive flag with no confirmation (rm -rf equivalent) |
| library | Breaking change in minor version bump |
Anti-patterns in pre-mortems
❌ Vague risks. "Performance might be a problem." Be specific: which operation, at what load, what's the SLO.
❌ Cosmic risks. "AWS could go down." Yes, but that's not actionable. Focus on what you can mitigate.
❌ Defensive list. Listing risks you've already mitigated to look thorough. Only list risks the current plan does NOT yet address.
❌ Skip the headline. Without the headline, the team won't believe the failure scenario is real.
When to skip
- nano project_size — pre-mortem is overhead.
- Pure refactor with full test coverage — guardrails already exist.
- Bug-fix with one-line repro — risk is well-bounded.
© avelikiy, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/pre-mortem of avelikiy/great_cto.
Open the folder on GitHubat commit 5d6e760
Compare with similar skills
Pre Mortem next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Pre Mortem this skillavelikiy/great_cto | 103 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Monitor CInrwl/nx | 29k | 6 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Terraform and OpenTofu Guideagentscope-ai/QwenPaw | 36k | 6 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Vercel Optimize Auditvercel-labs/agent-skills | 32k | 8 repos | ~4.3k | Automated safety check: Pass | None | |
| Analyze GitHub Action Logswithastro/astro | 63k | 1 repos | ~1.3k | Automated safety check: Pass | Custom licence | |
| Openclaw Live Updateropenclaw/openclaw | 392k | — | ~3.7k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Pre Mortem
What does Pre Mortem do?
Imagine the project has already shipped and failed catastrophically — work backwards from the failure to identify the most likely causes BEFORE building. Pre Mortem is an agent skill from avelikiy/great_cto. Imagine the project has already shipped and failed catastrophically — work backwards from the failure to identify the most likely causes BEFORE building.
When should I use Pre Mortem?
Pre Mortem fits situations like: devOps & Cloud work in your project.
How do I install Pre Mortem in Claude Code?
Run `npx skills add avelikiy/great_cto --skill pre-mortem -a claude-code`. Or copy the skill folder (skills/pre-mortem in avelikiy/great_cto) into .claude/skills/pre-mortem in your project. Claude Code loads it when a task matches its description.
How do I install Pre Mortem in Codex?
Run `npx skills add avelikiy/great_cto --skill pre-mortem -a codex`. Or copy the skill folder (skills/pre-mortem in avelikiy/great_cto) into .agents/skills/pre-mortem in your project. Codex loads it when a task matches its description.
Can I use Pre Mortem in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add avelikiy/great_cto --skill pre-mortem -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pre-mortem, .gemini/skills/pre-mortem, .github/skills/pre-mortem and .opencode/skills/pre-mortem in your project.
What does Pre Mortem need to run?
SKILL.md names no scripts, command-line tools or credentials: Pre Mortem is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write.
Does Pre Mortem access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Pre Mortem safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Pre Mortem use?
Pre Mortem is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Pre Mortem use?
About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Pre Mortem?
Skills that share tags, products or a category with Pre Mortem: Monitor CI (nrwl/nx, 29k stars), Terraform and OpenTofu Guide (agentscope-ai/QwenPaw, 36k stars), Vercel Optimize Audit (vercel-labs/agent-skills, 32k stars) and Analyze GitHub Action Logs (withastro/astro, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Pre Mortem?
avelikiy (a GitHub user) maintains it in avelikiy/great_cto, which has 103 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 9, 2026.
Source: avelikiy/great_cto on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.