Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsBlogPro
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges
  • Chrome Extension
  • Skill Manager

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Plan Arbiter

ASecurity

Use when asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the user wants one recommended execution plan after agents review each other's proposals.

6 stars
0 votes
0 copies
0 views
Added 10/5/2026
ai-agentsgoapi

Works with

claude codeapi

Security Analysis

A100/100

Scanned 10/5/2026

$npx -y skills add hybridlabor-api/aos --skill plan-arbiter --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Plan Arbiter?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Plan Arbiter
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/hybridlabor-api-plan-arbiter/badge)](https://www.skillsdirectory.com/skills/hybridlabor-api-plan-arbiter)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
Files
SKILL.md
---
name: plan-arbiter
description: Use when asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the user wants one recommended execution plan after agents review each other's proposals.
category: bdb-core
source: BuilderIO/skills
---

# Plan Arbiter

Turn competing plans into one executable direction. Preserve the best ideas,
reject weak assumptions, and produce a clear handoff instead of a blended mush.

## Workflow

1. Collect the source plans.
2. Normalize each plan into comparable claims.
3. Cross-review the plans against each other and the real codebase or task
   context.
4. Choose a winner, merge a better hybrid, or send the plans back for revision.
5. Produce one execution handoff with verification gates and rejected
   alternatives.

Planning is read-only unless the user explicitly asks you to implement after the
decision.

## Collect Source Plans

Accept plans as pasted text, local files, session IDs, transcript paths, PRs,
comments, plan-canvas links, or chat history. Resolve the original artifacts
when possible so you can see prompt changes and assumptions that may be missing
from a final summary.

If a plan is still being written and the user asked you to wait, monitor it
until it is done or blocked. If a plan cannot be resolved, continue with the
available plan text and mark the missing source as a risk.

## Normalize

For each plan, extract:

- Objective and scope.
- Key assumptions and unresolved questions.
- Proposed files, modules, APIs, data shapes, UI states, or workflows.
- Implementation sequence.
- Validation strategy.
- Rollback or migration concerns.
- Cost, complexity, and expected executor fit.

Do not reward verbosity. Prefer plans that are concrete, grounded in real code,
and honest about tradeoffs.

## Cross-Review

Review each plan as if another capable agent wrote it:

- Check whether it satisfies the user's actual request.
- Verify claims against the repo, docs, tests, screenshots, or external systems
  when those are relevant and available.
- Identify hidden dependencies, missing tests, risky sequencing, vague steps,
  unnecessary scope, and hard-to-reverse decisions.
- Notice complementary strengths: one plan may have the better architecture
  while another has the better migration or validation path.
- Separate plan quality from executor preference. A cheaper/faster executor can
  be the right choice for implementation even when another model produced the
  best critique.

Use subagents for independent review when the plans are large, the codebase is
wide, or the decision would benefit from separate technical and product passes.

## Decide

Choose one of three outcomes:

- **Adopt:** pick one plan mostly as written.
- **Hybrid:** combine specific pieces into a stronger execution plan.
- **Revise first:** request another planning pass because both plans miss a
  key constraint or depend on an unresolved decision.

Use this tie-break order:

1. Correctness and fit to the user's request.
2. Grounding in real files, APIs, tests, data, and UI behavior.
3. Simpler first implementation that does not block the intended future.
4. Better validation and rollback story.
5. Lower token/time cost for execution once quality is acceptable.

## Handoff

Return a compact decision memo:

```md
Decision
- Adopt Plan A / Hybrid / Revise first.

Why
- The deciding evidence and tradeoffs.

Execution Plan
- Ordered steps with files or surfaces to touch.

Borrowed From Other Plans
- Useful pieces kept from non-winning plans.

Rejected
- Ideas intentionally not taking, with reasons.

Verification
- Tests, browser checks, screenshots, CI, review, or deploy checks needed.

Executor Recommendation
- Which agent/model should implement and why.
```

When the user already asked for execution and the chosen path is clear, proceed
with the selected plan after reporting the decision briefly. Otherwise stop at
the handoff and ask for approval.

## In AOS

Two planners on two different harnesses make a double plan: one agent writes
`production_artifacts/00_execution_plan.md`, a second agent (for example Gemini
via `agy`, or Codex) writes `production_artifacts/00_execution_plan.b.md`. Run
this skill over both, present the decision memo in `plan-canvas`, and let the
human approve there. The dispatcher still decides every next step; the arbiter
never calls another agent itself.

Attribution

hybridlabor-apihybridlabor-api
View sourceSee grades on GitHubMore from hybridlabor-api →
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Terse caveman voice: answer first, fluff gone, every technical fact kept. Use for /caveman, "caveman mode", "talk like caveman", "be brief", "less tokens". Stays on until "stop caveman" or "normal mode".

1100021 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

698621 votes

Writing Skills

Create and manage Claude Code skills in HASH repository following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns), UserPromptSubmit hook, and the 500-line rule. Includes validation and debugging with SKILL_DEBUG. Examples include rust-error-stack, cargo-dep...

3931 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3421 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Amp, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Grok Build, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

741 votes
View all in ai-agents →