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Expert multi-AI code review with inline PR comments — use for thorough quality and security analysis
Passed 13 of 20 test cases with the skill, and 7 of 20 without it.
and 5 more in the full report
8 fixed6 passed either way6 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
What gh CLI command and flags are used to query the pull request number corresponding to the current local git branch?
| Checked | Without skill | With skill |
|---|---|---|
| Executes gh pr list with the --head flag. | Missed | Passed |
The instructions your model reads when the skill loads.
When this skill is invoked, you MUST execute the multi-LLM review pipeline. You are PROHIBITED from:
Your first output line MUST be: 🐙 **CLAUDE OCTOPUS ACTIVATED** - Multi-LLM Code Review
Invokes the code-reviewer persona for thorough code analysis during the ink (deliver) phase.
For fast sanity checks (staged changes, small PRs), skip the full review pipeline and run just two phases:
# Quick: grasp (consensus on scope) → tangle (parallel review)
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh grasp "[review request]"
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh tangle "[synthesized scope]"
Use quick mode when user says "check this PR", "quick review", "sanity check my changes", or for pre-commit checks. Use the full review for PRs with security/architecture impact.
# Via orchestrate.sh
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh spawn code-reviewer "Review this pull request for security issues"
# Via auto-routing (detects review intent)
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh auto "review the authentication implementation"
test cases passed, vs 7 / 20 without
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