Agent skill

Skill Ship

by nyldn in nyldn/claude-octopus

Package and finalize completed work for delivery — use when a feature is done and ready to ship

MITAuto-check passedSecurity

Install Skill Ship

skills CLI
$ npx skills add nyldn/claude-octopus --skill skill-ship -a claude-code

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

GitHub CLI
$ gh skill install nyldn/claude-octopus skill-ship --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/nyldn/claude-octopus.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skill-ship .claude/skills/skill-ship && 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
skill-ship
GitHub stars
4.2k
Used in
1 other repo
Token cost
~2.7k tokens
SKILL.md length
560 words
Files
2
Skills in repo
62
Repo updated
First seen
Licence
MIT

At a glance

Package and finalize completed work for delivery — use when a feature is done and ready to ship

  • Works in 6 steps: Verify Project Ready to Ship → Multi-AI Security Audit → Capture Lessons Learned → …
  • A feature is done and ready to ship
  • SKILL.md covers When to Use, The Process, MANDATORY COMPLIANCE and Error Handling, plus 5 more sections
  • Calls git

What it does

Skill Ship is an agent skill from nyldn/claude-octopus. Package and finalize completed work for delivery — use when a feature is done and ready to ship

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Security. The repository describes itself as: Run multiple AI models against the same research, design, or coding task. Surface disagreements before you ship. The licence is MIT.

When your agent uses it

  • A feature is done and ready to ship

Example prompts

  • “/skill-ship”

Workflow steps

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

  1. Verify Project Ready to Ship
  2. Multi-AI Security Audit
  3. Capture Lessons Learned
  4. Archive Project State
  5. Create Delivery Summary
  6. Display Completion

What it can do on your machine

Read from SKILL.md and the folder at commit 4d152db. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, 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 no API keys, tokens, secrets or passwords.

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

Context cost

Skill Ship loads about 2.7k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 560 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~27
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

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 nyldn/claude-octopus at commit 4d152db, republished under its MIT licence (© nyldn). 560 words, ~2,652 tokens.

Download SKILL.mdSave it as .claude/skills/skill-ship/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
skill-ship
description
Package and finalize completed work for delivery — use when a feature is done and ready to ship
disable-model-invocation
true

Host: Codex CLI — This skill was designed for Claude Code and adapted for Codex. Cross-reference commands use installed skill names in Codex rather than /octo:* slash commands. Use the active Codex shell and subagent tools. Do not claim a provider, model, or host subagent is available until the current session exposes it. For host tool equivalents, see skills/blocks/codex-host-adapter.md.

Ship Project - Multi-AI Delivery Validation

Finalize and deliver completed work with Multi-AI security audit, lessons capture, and archival.

Core principle: Verify ready -> Multi-AI audit -> Capture lessons -> Archive -> Ship.

When to Use

Use this skill when user asks:

  • "Ship the project" or "We're done"
  • "Finalize this" or "Let's deliver"
  • "Complete the project" or "Ready to ship"
  • "Mark as shipped" or "Time to deliver"

Do NOT use for:

  • Code review (use /octo:review or flow-deliver)
  • Implementation (use /octo:develop)
  • Research (use /octo:research)

The Process

Phase 1: Verify Project Ready to Ship
Step 1: Check .octo/ Exists
bash
if [[ ! -d ".octo" ]]; then
    echo "No project initialized"
    exit 1
fi

If .octo/ does not exist:

markdown
## Cannot Ship

**Status:** No project initialized

No Claude Octopus project found in this directory.

Run `/octo:embrace [description]` to start a new project.

STOP. Do not proceed.

Step 2: Read STATE.md Status
bash
# Check if STATE.md exists and read status
if [[ -f ".octo/STATE.md" ]]; then
    # Read current status
    STATUS=$(grep -E "^status:" .octo/STATE.md | cut -d':' -f2 | xargs || echo "unknown")
    CURRENT_PHASE=$(grep -E "^current_phase:" .octo/STATE.md | cut -d':' -f2 | xargs || echo "unknown")
else
    STATUS="unknown"
    CURRENT_PHASE="unknown"
fi

echo "Status: $STATUS"
echo "Current Phase: $CURRENT_PHASE"
Step 3: Validate Ready State

Ship is allowed when:

  • status = "complete" OR
  • current_phase = "4" (Deliver phase) OR
  • All four phases have entries in STATE.md history

If not ready:

markdown
## Project Not Ready to Ship

**Current Status:** {status}
**Current Phase:** {current_phase}

### To prepare for shipping:

1. Complete remaining phases:
   - [ ] Phase 1: Discover - Use `/octo:discover`
   - [ ] Phase 2: Define - Use `/octo:define`
   - [ ] Phase 3: Develop - Use `/octo:develop`
   - [ ] Phase 4: Deliver - Use `/octo:deliver`

2. Or override with: "ship anyway" (not recommended)

STOP unless user says "ship anyway".

Phase 2: Multi-AI Security Audit
Step 1: Display Visual Indicators
bash
# Check provider availability
command -v codex &> /dev/null && codex_status="Available" || codex_status="Not installed"
command -v agy &> /dev/null && agy_status="Available" || agy_status="Not installed"

Output:

markdown
## Multi-AI Security Audit

**Providers:**
- Codex CLI: ${codex_status} - Code security analysis
- Antigravity CLI: ${agy_status} - Additional external-model challenge
- Claude: Available - Synthesis and final validation

**Estimated Time:** 3-5 minutes
**Estimated Cost:** 0.02-0.08 USD
Step 2: Execute orchestrate.sh Security Audit

You MUST execute this via native shell command tool:

bash
# Run Multi-AI security audit for delivery
"${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh" ink "Security audit for delivery - comprehensive review of all code changes for production readiness"

MANDATORY COMPLIANCE

CRITICAL: You are PROHIBITED from:

  • Skipping Multi-AI validation
  • Doing single-provider analysis instead
  • Claiming you're "simulating" the audit
  • Proceeding without running orchestrate.sh
Step 3: Verify Audit Completed
bash
# Find the latest validation file
VALIDATION_FILE=$(find ~/.claude-octopus/results -name "ink-validation-*.md" -mmin -10 2>/dev/null | head -n1)

if [[ -z "$VALIDATION_FILE" ]]; then
    echo "AUDIT FAILED: No validation file found"
    exit 1
fi

echo "AUDIT COMPLETE: $VALIDATION_FILE"
Step 4: Display Audit Summary

Read validation file and present:

  • Overall status (PASSED / PASSED WITH WARNINGS / FAILED)
  • Quality score
  • Critical issues (must fix before ship)
  • Warnings (should fix)

If FAILED with critical issues:

markdown
## Audit Failed - Cannot Ship

Critical issues must be resolved before shipping:

1. [Issue 1 from validation]
2. [Issue 2 from validation]

Resolve issues and run `/octo:ship` again.

STOP if critical issues found.

Phase 3: Capture Lessons Learned
Step 1: Ask User for Lessons
markdown
## Lessons Learned

Before finalizing, let's capture what we learned from this project.

**Please answer the following:**

1. **What went well?** (What worked better than expected?)

2. **What could improve?** (What would you do differently?)

3. **Key learnings?** (What insights will you carry forward?)

*Reply with your answers, or type "skip" to proceed without capturing lessons.*

Wait for user response.

Step 2: Append to LESSONS.md

If user provides lessons (not "skip"):

bash
# Generate timestamp
TIMESTAMP=$(date '+%Y-%m-%d')

# Ensure LESSONS.md exists
touch .octo/LESSONS.md

# Append lessons
cat >> .octo/LESSONS.md << EOF

## ${TIMESTAMP} - Project Delivery

### What Went Well
- ${USER_WHAT_WENT_WELL}

### What Could Improve
- ${USER_WHAT_COULD_IMPROVE}

### Key Learnings
- ${USER_KEY_LEARNINGS}

EOF

Count total lessons:

bash
LESSON_COUNT=$(grep -c "^## " .octo/LESSONS.md 2>/dev/null || echo "0")
echo "Total lessons captured: $LESSON_COUNT"
Phase 4: Archive Project State
Step 1: Create Archive Directory
bash
# Generate timestamp for archive
ARCHIVE_TIMESTAMP=$(date +%Y%m%d-%H%M%S)
ARCHIVE_DIR=".octo/archive/${ARCHIVE_TIMESTAMP}"

# Create archive directory
mkdir -p "$ARCHIVE_DIR"
Show full SKILL.md (231 more words)Show less
Step 2: Copy State Files to Archive
bash
# Archive STATE.md if exists
if [[ -f ".octo/STATE.md" ]]; then
    cp .octo/STATE.md "$ARCHIVE_DIR/"
fi

# Archive PROJECT.md if exists
if [[ -f ".octo/PROJECT.md" ]]; then
    cp .octo/PROJECT.md "$ARCHIVE_DIR/"
fi

# Archive ROADMAP.md if exists
if [[ -f ".octo/ROADMAP.md" ]]; then
    cp .octo/ROADMAP.md "$ARCHIVE_DIR/"
fi

# Archive ISSUES.md if exists
if [[ -f ".octo/ISSUES.md" ]]; then
    cp .octo/ISSUES.md "$ARCHIVE_DIR/"
fi

echo "Archived to: $ARCHIVE_DIR"

IMPORTANT: NEVER archive LESSONS.md - lessons are preserved across projects.

Step 3: Verify Archive
bash
# List archived files
ls -la "$ARCHIVE_DIR"
Phase 5: Create Delivery Summary
Step 1: Update STATE.md
bash
# Update status to shipped
sed -i '' 's/^status:.*/status: shipped/' .octo/STATE.md 2>/dev/null || \
    sed -i 's/^status:.*/status: shipped/' .octo/STATE.md

# Append history entry
cat >> .octo/STATE.md << EOF

## History - $(date '+%Y-%m-%d %H:%M')

- **Event:** Project shipped
- **Archive:** .octo/archive/${ARCHIVE_TIMESTAMP}/
- **Validation:** ${VALIDATION_FILE}

EOF
Step 2: Create Shipped Checkpoint
bash
# Create git checkpoint tag
CHECKPOINT_TAG="octo-checkpoint-shipped-${ARCHIVE_TIMESTAMP}"

git tag -a "$CHECKPOINT_TAG" -m "Project shipped - $(date '+%Y-%m-%d %H:%M:%S')"

echo "Checkpoint created: $CHECKPOINT_TAG"
Step 3: Count Metrics
bash
# Count resolved issues
ISSUES_RESOLVED=$(grep -c "^\- \[x\]" .octo/ISSUES.md 2>/dev/null || echo "0")

# Count total lessons
LESSONS_COUNT=$(grep -c "^## " .octo/LESSONS.md 2>/dev/null || echo "0")

echo "Issues resolved: $ISSUES_RESOLVED"
echo "Lessons captured: $LESSONS_COUNT"
Phase 6: Display Completion

Present final summary:

markdown
## Project Shipped!

**Delivered:** {timestamp}
**Phases Completed:** 4/4
**Issues Resolved:** {ISSUES_RESOLVED}
**Lessons Captured:** {LESSONS_COUNT}

### Multi-AI Audit Summary

- **Security Score:** {score}/100
- **Quality Score:** {score}/100
- **Providers Used:** Claude plus available external providers

### Archive

Location: `.octo/archive/{ARCHIVE_TIMESTAMP}/`

Contents:
- STATE.md
- PROJECT.md
- ROADMAP.md
- ISSUES.md

### Checkpoint

Tag: `{CHECKPOINT_TAG}`

Restore with: `/octo:rollback {CHECKPOINT_TAG}`


**To start a new project:** `/octo:embrace`

*Multi-AI validation powered by Claude Octopus*
*Providers: Codex | Antigravity | Claude*

Error Handling

ErrorResolution
No .octo/ directorySuggest /octo:embrace
Project not readyShow remaining phases
orchestrate.sh failsShow error logs, suggest retry
Critical audit issuesBlock ship, show issues
Git tag failsWarn but continue (non-blocking)

Safety Measures

MeasureImplementation
Pre-ship auditorchestrate.sh Multi-AI validation required
Lessons preservationLESSONS.md never archived, always preserved
Archive before shipState files copied to archive directory
Git checkpointTag created for rollback capability
No file deletionArchive copies, doesn't delete source files

Integration with Other Skills

With /octo:deliver
User runs /octo:deliver to validate
→ Deliver phase complete
→ User runs /octo:ship to finalize
With /octo:rollback
User ships project
→ Checkpoint created
→ Later: /octo:rollback octo-checkpoint-shipped-*
With /octo:status
After ship: status shows "shipped"
→ Suggests /octo:embrace for new project

Red Flags - Never Do

ActionWhy It's Wrong
Skip Multi-AI auditSecurity vulnerabilities missed
Archive LESSONS.mdLoses accumulated project knowledge
Delete source filesShould copy, not move
Ship without ready checkIncomplete work shipped
Skip checkpoint creationNo rollback recovery path

Quick Reference

StepCommandPurpose
1Check .octo/STATE.mdVerify ready to ship
2orchestrate.sh inkMulti-AI security audit
3Ask userCapture lessons learned
4mkdir + cpArchive state files
5Update STATE.mdMark as shipped
6git tagCreate shipped checkpoint

The Bottom Line

Ship → Ready + Audit passed + Lessons captured + Archived + Checkpoint created
Otherwise → Not shipped

Verify ready. Run Multi-AI audit. Capture lessons. Archive state. Create checkpoint. Ship.

© nyldn, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/skill-ship of nyldn/claude-octopus.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 4d152db

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in nyldn/claude-octopus, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Security Alert Triageelastic/agent-skills5921 repos~3.5kAutomated safety check: NotesApache-2.0

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Categories

Questions about Skill Ship

What does Skill Ship do?

Package and finalize completed work for delivery — use when a feature is done and ready to ship. Skill Ship is an agent skill from nyldn/claude-octopus.

When should I use Skill Ship?

Skill Ship fits situations like: A feature is done and ready to ship.

How do I install Skill Ship in Claude Code?

Run `npx skills add nyldn/claude-octopus --skill skill-ship -a claude-code`. Or copy the skill folder (skills/skill-ship in nyldn/claude-octopus) into .claude/skills/skill-ship in your project. Claude Code loads it when a task matches its description.

How do I install Skill Ship in Codex?

Run `npx skills add nyldn/claude-octopus --skill skill-ship -a codex`. Or copy the skill folder (skills/skill-ship in nyldn/claude-octopus) into .agents/skills/skill-ship in your project. Codex loads it when a task matches its description.

Can I use Skill Ship 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 nyldn/claude-octopus --skill skill-ship -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-ship, .gemini/skills/skill-ship, .github/skills/skill-ship and .opencode/skills/skill-ship in your project.

What does Skill Ship need to run?

Going by SKILL.md and its folder, Skill Ship needs the command-line tools its instructions call (git).

Does Skill Ship access the network?

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

Is Skill Ship 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 Skill Ship use?

Skill Ship 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 Skill Ship use?

About 2.7k tokens (SKILL.md is roughly 11k 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 Skill Ship?

Skills that share tags, products or a category with Skill Ship: Fla Ascend Performance (fla-org/flash-linear-attention, 5.8k stars), Deepsec Documentation Guide (vercel-labs/deepsec, 8.1k stars), Skill Scanner (getsentry/skills, 1k stars) and Serenity Aleabitoreddit (yan-labs/serenity-aleabitoreddit, 480 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skill Ship?

nyldn (a GitHub user) maintains it in nyldn/claude-octopus, which has 4,182 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on October 7, 2026.

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