Agent skill

Ops Yolo

by davepoon in davepoon/buildwithclaude

YOLO mode. An agent skill from davepoon/buildwithclaude.

MITAuto-check: notesAI & LLM Engineering

Install Ops Yolo

skills CLI
$ npx skills add davepoon/buildwithclaude --skill ops-yolo -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davepoon/buildwithclaude ops-yolo --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davepoon/buildwithclaude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/claude-ops/skills/ops-yolo .claude/skills/ops-yolo && rm -rf skills-src

Use ~/.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/

Facts

Skill name
ops-yolo
GitHub stars
3.6k
Token cost
~2.9k tokens
SKILL.md length
980 words
Files
1
Skills in repo
245
Repo updated
First seen
Licence
MIT

At a glance

YOLO mode. An agent skill from davepoon/buildwithclaude.

  • Works in 4 steps: Pre-gather ALL data → Spawn 4 C-suite agents in parallel → Hard Truths Report (orchestrator… → …
  • Tasks that involve Computer vision
  • SKILL.md covers Runtime Context, CLI/API Reference, Agent Teams support and Phase 1 — Pre-gather ALL data, plus 4 more sections
  • Calls gh, aws and jq; needs GITHUB_TOKEN and SENTRY_AUTH_TOKEN

What it does

Ops Yolo is an agent skill from davepoon/buildwithclaude. YOLO mode. Spawns 4 parallel C-suite agents (CEO, CTO, CFO, COO). Each analyzes the business from their perspective using ALL available data. Produces unfiltered Hard Truths report. After user types YOLO, autonomously runs the business for a day using /loop.

Its SKILL.md is about 2.9k 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 AI & LLM Engineering, covering Computer vision. It works with Amazon Web Services. The repository describes itself as: A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins, and Marketplace collections to extend Claude Code, Claude Desktop, Agent SDK and OpenClaw. The licence is MIT.

When your agent uses it

  • Tasks that involve Computer vision

Example prompts

  • “/ops-yolo”

Requirements

  • A credential in GITHUB_TOKEN
  • A credential in SENTRY_AUTH_TOKEN
  • Pre-approved tools (allowed-tools): Bash, Read, Grep, Glob, Skill, Agent, AskUserQuestion, TeamCreate, SendMessage, TaskCreate, TaskUpdate, TaskList, EnterPlanMode, ExitPlanMode, CronCreate, CronList, CronDelete, Monitor, WebFetch, WebSearch, mcp__linear__list_issues, mcp__claude_ai_Vercel__list_deployments, mcp__claude_ai_Slack__slack_search_public_and_private, mcp__claude_ai_Gmail__search_threads

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Pre-gather ALL data
  2. Spawn 4 C-suite agents in parallel
  3. Hard Truths Report (orchestrator synthesis)
  4. YOLO Autonomous Mode

What it can do on your machine

Read from SKILL.md and the folder at commit 10bfc43. 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:

    • Bash
    • Read
    • Grep
    • Glob
    • Skill
    • Agent
    • AskUserQuestion
    • TeamCreate
    • SendMessage
    • TaskCreate

    …and 14 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh
    • aws
    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh and aws, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GITHUB_TOKEN
    • SENTRY_AUTH_TOKEN
    • LINEAR_API_KEY
    • AWS_ACCESS_KEY_ID

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ops Yolo loads about 2.9k tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 980 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, Grep, Glob, Skill, Agent, AskUserQuestion, TeamCreate, SendMessage, TaskCreate, TaskUpda

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 davepoon/buildwithclaude at commit 10bfc43, republished under its MIT licence (© davepoon). 980 words, ~2,893 tokens.

Download SKILL.mdSave it as .claude/skills/ops-yolo/SKILL.md (or your agent's skills folder).
name
ops-yolo
description
YOLO mode. Spawns 4 parallel C-suite agents (CEO, CTO, CFO, COO). Each analyzes the business from their perspective using ALL available data. Produces unfiltered Hard Truths report. After user types YOLO, autonomously runs the business for a day using /loop.
allowed-tools
Bash, Read, Grep, Glob, Skill, Agent, AskUserQuestion, TeamCreate, SendMessage, TaskCreate, TaskUpdate, TaskList, EnterPlanMode, ExitPlanMode, CronCreate, CronList, CronDelete, Monitor, WebFetch, WebSearch, mcp__linear__list_issues, mcp__claude_ai_Vercel__list_deployments, mcp__claude_ai_Slack__slack_search_public_and_private, mcp__claude_ai_Gmail__search_threads
argument-hint
[YOLO|analyze|report]
effort
high
model
claude-opus-4-6
maxTurns
50

Runtime Context

Before YOLO analysis, load:

  1. Preferences: cat ${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json — read owner, timezone, yolo_enabled, all channel configs
  2. Daemon health: cat ${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.json — all services must be healthy for comprehensive analysis
  3. Secrets: Resolve ALL keys via env → Doppler → password manager: GITHUB_TOKEN, SENTRY_AUTH_TOKEN, LINEAR_API_KEY, AWS_ACCESS_KEY_ID
  4. Ops memories: Load ALL files from ${CLAUDE_PLUGIN_DATA_DIR}/memories/ — contact profiles, preferences, topics, donts. YOLO agents need maximum context.

OPS ► YOLO MODE

CLI/API Reference

aws CLI (Cost Explorer)
CommandUsageOutput
aws ce get-cost-and-usage --time-period Start=<YYYY-MM-DD>,End=<YYYY-MM-DD> --granularity MONTHLY --metrics "UnblendedCost" --output jsonCurrent month spendCost JSON
gh CLI (GitHub)
CommandUsageOutput
gh pr list --repo <owner/repo> --json number,title,statusCheckRollup,reviewDecision,mergeable,isDraftOpen PRs with statusJSON array
gh pr merge <n> --repo <repo> --squash --adminSquash merge PRMerge result
gh run list --limit 20 --json status,conclusion,name,headBranch,createdAtRecent CI runsJSON array

Agent Teams support

If CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set, use Agent Teams instead of fire-and-forget subagents for the C-suite analysis (Phase 2). This enables:

  • Agents can share findings mid-analysis (CEO discovers a revenue blocker → CFO factors it into ROI)
  • You can steer agents if early findings change priorities
  • Agents coordinate on the consensus recommendation

Team setup (only when flag is enabled):

TeamCreate("yolo-csuite")
Agent(team_name="yolo-csuite", name="ceo", subagent_type="ops:yolo-ceo", ...)
Agent(team_name="yolo-csuite", name="cto", subagent_type="ops:yolo-cto", ...)
Agent(team_name="yolo-csuite", name="cfo", subagent_type="ops:yolo-cfo", ...)
Agent(team_name="yolo-csuite", name="coo", subagent_type="ops:yolo-coo", ...)

After initial analysis, use SendMessage(to="cto", content="CFO flagged $400/mo in waste — does this change your tech-debt ranking?") or similar to cross-pollinate findings between peer agents. The main /ops:yolo orchestrator (this skill) then reads all four analysis files (ceo-analysis.md, cto-analysis.md, cfo-analysis.md, coo-analysis.md) and synthesizes them into the Hard Truths report. yolo-ceo is a parallel peer, not the synthesizer.

If the flag is NOT set, fall back to standard parallel subagents (fire-and-forget, no mid-task steering).

Phase 1 — Pre-gather ALL data

Run all of these simultaneously:

${CLAUDE_PLUGIN_ROOT}/bin/ops-infra 2>/dev/null || echo '{}'
${CLAUDE_PLUGIN_ROOT}/bin/ops-git 2>/dev/null || echo '[]'
${CLAUDE_PLUGIN_ROOT}/bin/ops-prs 2>/dev/null || echo '[]'
${CLAUDE_PLUGIN_ROOT}/bin/ops-ci 2>/dev/null || echo '[]'
${CLAUDE_PLUGIN_ROOT}/bin/ops-unread 2>/dev/null || echo '{}'
aws ce get-cost-and-usage --time-period "Start=$(date +%Y-%m-01),End=$(date +%Y-%m-%d)" --granularity MONTHLY --metrics "UnblendedCost" --output json 2>/dev/null || echo '{}'
cat "${CLAUDE_PLUGIN_ROOT}/scripts/registry.json" 2>/dev/null || echo '{}'
${CLAUDE_PLUGIN_ROOT}/bin/ops-external 2>/dev/null || echo '[]'
for d in $(jq -r '.projects[] | select(.gsd == true) | .paths[]' "${CLAUDE_PLUGIN_ROOT}/scripts/registry.json" 2>/dev/null); do
  expanded="${d/#\~/$HOME}"
  [ -f "$expanded/.planning/STATE.md" ] && echo "=== $(basename $expanded) ===" && cat "$expanded/.planning/STATE.md" && echo "---"
done

Phase 2 — Spawn 4 C-suite agents in parallel

Spawn these 4 agents simultaneously using all pre-gathered data as context. Each writes their analysis to a file in /tmp/yolo-[session]/:

Agent 1 — CEO (Strategic)

Uses agents/yolo-ceo.md. Writes /tmp/yolo-[session]/ceo-analysis.md.

  • What's the #1 thing blocking growth right now?
  • Are we building the right things?
  • Where are we wasting time vs. creating value?
  • What would you tell an investor today, unfiltered?
Agent 2 — CTO (Technical)

Uses agents/yolo-cto.md. Writes /tmp/yolo-[session]/cto-analysis.md.

  • What's the worst technical debt that will bite us?
  • Which services are time-bombs?
  • Is the team/architecture set up to scale?
  • What corners were cut that need fixing now?
Agent 3 — CFO (Financial)

Uses agents/yolo-cfo.md. Writes /tmp/yolo-[session]/cfo-analysis.md.

  • Actual burn rate vs. runway
  • Which AWS services are waste?
  • When do we hit zero if nothing changes?
  • What's the ROI on current work?
Agent 4 — COO (Operations)

Uses agents/yolo-coo.md. Writes /tmp/yolo-[session]/coo-analysis.md.

  • What's falling through the cracks right now?
  • Which processes are broken?
  • What's the top execution risk this week?
  • What should be automated that isn't?

Phase 3 — Hard Truths Report (orchestrator synthesis)

This skill (the main orchestrator) is the synthesizer — NOT yolo-ceo. After all 4 parallel agents complete and have written their analysis files to /tmp/yolo-[session]/{ceo,cto,cfo,coo}-analysis.md, read all four files here in the main context and synthesize them into a unified report:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 YOLO ► HARD TRUTHS REPORT — [date]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

 CEO: [1-2 brutal strategic truths]

 CTO: [1-2 brutal technical truths]

 CFO: [1-2 brutal financial truths]

 COO: [1-2 brutal operational truths]

──────────────────────────────────────────────────────
 CONSENSUS: The #1 thing that matters today is:
 [single most important action, no sugar-coating]
──────────────────────────────────────────────────────

 Full analysis files saved to:
 /tmp/yolo-[session]/ceo-analysis.md
 /tmp/yolo-[session]/cto-analysis.md
 /tmp/yolo-[session]/cfo-analysis.md
 /tmp/yolo-[session]/coo-analysis.md

──────────────────────────────────────────────────────
 Type YOLO to hand over the controls.
 I'll run your business autonomously for the next day.
 This means: closing inbox, merging ready PRs,
 fixing fires, advancing GSD phases, triaging issues.

 Or pick an analysis to read:
──────────────────────────────────────────────────────

Use batched AskUserQuestion calls (max 4 options each):

AskUserQuestion call 1:

  [Read CEO analysis]
  [Read CTO analysis]
  [Read CFO analysis]
  [More...]

AskUserQuestion call 2 (only if "More..."):

  [Read COO analysis]
  [Execute top recommendation now]
  [Type YOLO to go autonomous]

Show full SKILL.md (475 more words)Show less

Phase 4 — YOLO Autonomous Mode

If user types YOLO (all caps), enter autonomous mode via /loop.

Before starting, use AskUserQuestion to confirm scope:

YOLO mode will autonomously execute these steps:
  1. Inbox — reply to humans, archive automated
  2. Fires — fix CRITICAL/HIGH production issues
  3. PRs — merge ready PRs (CI green, approved)
  4. Triage — auto-resolve confirmed-fixed issues
  5. GSD — advance highest-priority phase
  6. Linear — sync sprint board
  7. Deploy — trigger pending deploys
  8. Report — summary

  [Run all 8 steps]  [Pick which steps to run]  [Cancel]

If user picks "Pick which steps", show steps as multiSelect via batched AskUserQuestion calls (max 4 options each):

Call 1: [Inbox], [Fires], [PRs], [More steps...] Call 2 (if "More steps..."): [Triage], [GSD], [Linear], [More steps...] Call 3 (if "More steps..."): [Deploy], [Report], [Done selecting]

Run the selected steps in sequence, reporting after each step.

Per-step confirmations (use AskUserQuestion before EACH destructive action):

  • Inbox: Show drafted replies and ask [Send all N replies] / [Review each one] / [Skip inbox] before sending any messages
  • Fires: Show proposed fix and ask [Dispatch fix agent] / [Skip] before each agent dispatch
  • PRs: Show PR list and ask [Merge all N ready PRs] / [Pick which ones] / [Skip] before merging
  • Triage: Show issues to close and ask [Auto-resolve all N confirmed-fixed] / [Review each] / [Skip] before closing
  • Deploy: Show pending deploys and ask [Deploy all] / [Pick which] / [Skip] before triggering
  • Infrastructure changes: For EVERY destructive infra action (delete ALB, stop RDS, disable Multi-AZ, purge images, etc.), present the specific action with context from the C-suite reports and ask [Execute] / [Skip] individually. NEVER batch destructive infra actions.

Report-driven execution: When the user approves executing recommendations from the Hard Truths report:

  1. Read ALL C-suite analysis files (/tmp/yolo-[session]/*.md)
  2. Extract specific actionable items marked with ⚠️ REQUIRES CONFIRMATION
  3. Present each action individually via AskUserQuestion with the exact command that will run, the expected outcome, and the source report (CTO/CFO/COO)
  4. Only execute after explicit per-action approval
  5. After each action, verify the result and report back before proceeding to the next

After each step, check if new fires have appeared before proceeding. Report final summary when done.

If $ARGUMENTS is analyze or empty, go straight to Phase 1. If $ARGUMENTS is YOLO, skip to Phase 4. If $ARGUMENTS is report, skip to Phase 3 (reads existing analysis files if present).


Native tool usage

Tasks — progress tracking

Use TaskCreate at the start of Phase 4 to create a task for each YOLO step. Update with TaskUpdate as each completes. This gives the user a live progress view across the autonomous run.

PlanMode — review before autonomous

Before Phase 4 execution, use EnterPlanMode to present the full execution plan. The user reviews what YOLO will do, approves or modifies, then ExitPlanMode to begin execution.

Cron — schedule daily YOLO

After Phase 4 completes, offer to schedule recurring YOLO via AskUserQuestion:

  [Schedule daily YOLO at 9am]  [Schedule weekly Monday briefing]  [No schedule]

Use CronCreate if selected. Use CronList/CronDelete to manage existing schedules.

Monitor — live CI/deploy watching

When YOLO dispatches fix agents or triggers deploys, use Monitor to stream CI output in real-time instead of polling with sleep loops.

WebFetch/WebSearch — enrichment

Use WebFetch to pull Grafana dashboards, Sentry event details, or AWS status pages when MCPs are unavailable. Use WebSearch to find context on production errors (e.g., known AWS outages).

© davepoon, 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 plugins/claude-ops/skills/ops-yolo of davepoon/buildwithclaude.

Open the folder on GitHubat commit 10bfc43

Compare with similar skills

Ops Yolo 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.

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CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs13k8 repos~1.7kAutomated safety check: PassMIT
SageMaker Serving Image Selectionhuggingface/skills11k1 repos~4.6kAutomated safety check: PassApache-2.0
Yolo Master AgentTencent/YOLO-Master742—~755Automated safety check: PassAGPL-3.0
Video Understandjjyaoao/HelloAgents3.2k1 repos~6.2kAutomated safety check: PassMIT

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Questions about Ops Yolo

What does Ops Yolo do?

YOLO mode. An agent skill from davepoon/buildwithclaude. Ops Yolo is an agent skill from davepoon/buildwithclaude. YOLO mode.

When should I use Ops Yolo?

Ops Yolo fits situations like: tasks that involve Computer vision.

How do I install Ops Yolo in Claude Code?

Run `npx skills add davepoon/buildwithclaude --skill ops-yolo -a claude-code`. Or copy the skill folder (plugins/claude-ops/skills/ops-yolo in davepoon/buildwithclaude) into .claude/skills/ops-yolo in your project. Claude Code loads it when a task matches its description.

How do I install Ops Yolo in Codex?

Run `npx skills add davepoon/buildwithclaude --skill ops-yolo -a codex`. Or copy the skill folder (plugins/claude-ops/skills/ops-yolo in davepoon/buildwithclaude) into .agents/skills/ops-yolo in your project. Codex loads it when a task matches its description.

Can I use Ops Yolo 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 davepoon/buildwithclaude --skill ops-yolo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ops-yolo, .gemini/skills/ops-yolo, .github/skills/ops-yolo and .opencode/skills/ops-yolo in your project.

What does Ops Yolo need to run?

Going by SKILL.md and its folder, Ops Yolo needs the command-line tools its instructions call (gh, aws and jq) and credentials named GITHUB_TOKEN, SENTRY_AUTH_TOKEN, LINEAR_API_KEY and AWS_ACCESS_KEY_ID. Our summary lists: A credential in GITHUB_TOKEN; A credential in SENTRY_AUTH_TOKEN. Its frontmatter pre-approves these tools: Bash, Read, Grep, Glob, Skill, Agent, AskUserQuestion, TeamCreate, SendMessage, TaskCreate, TaskUpdate, TaskList, EnterPlanMode, ExitPlanMode, CronCreate, CronList, CronDelete, Monitor, WebFetch, WebSearch, mcp__linear__list_issues, mcp__claude_ai_Vercel__list_deployments, mcp__claude_ai_Slack__slack_search_public_and_private, mcp__claude_ai_Gmail__search_threads.

Does Ops Yolo access the network?

SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Ops Yolo safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Ops Yolo use?

Ops Yolo 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 Ops Yolo use?

About 2.9k tokens (SKILL.md is roughly 12k 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 Ops Yolo?

Skills that share tags, products or a category with Ops Yolo: Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), SageMaker Serving Image Selection (huggingface/skills, 11k stars) and Yolo Master Agent (Tencent/YOLO-Master, 742 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ops Yolo?

davepoon (a GitHub user) maintains it in davepoon/buildwithclaude, which has 3,604 GitHub stars. The repository holds 245 skills in this directory. The repository was last updated on October 6, 2026.

Source: davepoon/buildwithclaude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.