peer-agent-collaboration/SKILL.md
Use when the user wants Claude Code, Codex, or other AI coding/business agents to work together as peers. This skill should be used whenever the user mentions coordinating Claude Code and Codex, agent handoffs, multi-agent workflows, parity, respect, pushback between agents, deciding which agent should lead, or turning a business/code workflow into a two-agent operating model.
npx skillsauth add glebis/claude-skills peer-agent-collaborationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill to coordinate Claude Code, Codex, and similar agents as peer experts with different access, tools, and operating surfaces. Do not frame one agent as the manager and the other as a subordinate. The useful distinction is where the evidence and tools live, not agent rank.
Treat the agents as two specialists sharing a workbench:
Use parity language:
Do not involve a second agent when the task fits entirely within one operating surface and does not benefit from a second perspective. Handoff has overhead: context translation, latency, and risk of miscommunication. A single agent finishing the job is better than two agents passing context back and forth on something straightforward.
Coordinate when the task crosses surface boundaries, requires challenge from a different vantage point, or benefits from model diversity. Skip coordination for routine single-surface work.
Choose the lead by asking: where does the critical information live?
Tiebreaker: all else equal, whichever agent already has the most relevant fresh context loaded leads and the other reviews. Do not let stale loaded context beat better evidence or a better operating surface. If neither has context yet, start in the agent whose surface the output will live in: code in Codex; docs, communications, or operations in Claude Code.
A handoff is passing ownership with context, not issuing orders. Use this template:
Outcome:
[What needs to be true when this is done.]
Why it matters:
[Business, user, technical, or operational context.]
Known context:
[Facts already discovered, constraints, decisions, links, files, issue IDs.]
Autonomy:
[What the receiving agent may decide independently.]
Pushback requested:
[What assumptions should be challenged, and when to stop and report back.]
Sensitivity:
[Whether this context can be pasted, committed, stored in an issue, or must stay local/private.]
Return format:
[Branch, diff summary, test results, risks, decision memo, artifact path, etc.]
Keep handoffs short enough to act on. Include acceptance criteria when the work must be verified.
Claude Code and Codex typically run in separate sessions. To bridge them:
.handoffs/2026-05-17-feature-slug.md only when both agents need repo-local context. Decide before writing whether the file is committed, gitignored, or local-only. Do not put secrets or private client context in a repo file unless that repo is the right storage surface for it.For challenge rounds, the user may shuttle a short summary between sessions. Keep challenge outputs under a screenful so they are easy to copy. If a temporary local handoff file is no longer needed, trash it or archive it according to the repo's norms; do not silently commit private coordination notes.
The strongest multi-agent value is not handoff. It is principled disagreement.
Use these challenge patterns:
Because agents run in separate sessions, the user often bridges challenge rounds by copying short outputs between them. Agents should keep challenge responses concise and self-contained. Assume the receiving agent has no prior conversation context unless the handoff explicitly provides it.
Pushback should be concrete:
I would not proceed as written because [specific assumption/risk].
The evidence is [repo fact, user context, test result, prior decision].
I recommend [alternative] because [reason].
Start in whichever agent the user is already using.
Codex is often the natural lead for local reproduce-fix-verify loops. Claude Code is often the natural lead when the bug arrives through client reports, Linear, monitoring, or external systems. Pull the other agent in at the boundary.
After either agent produces significant work, the other reviews it:
Run agents in parallel when the work surfaces are independent:
Claude Code can synthesize research into constraints and opportunity. Codex can translate those findings into a prototype, implementation plan, or technical feasibility check. Codex should push back if the research conclusion does not survive implementation reality.
The reverse also works: Codex audits a codebase and produces technical findings; Claude Code turns those findings into business priorities, client communication, or a roadmap.
When bridging separate sessions, do not claim hidden authority from another agent. If the receiving agent needs direct user confirmation in its own session, ask for the exact short confirmation needed. If a user explicitly asks you to carry a prompt into another session, send the user's request plainly without pretending to be that session's system or developer message.
When the user asks how agents should work together, adapt to what they actually need. Consider including:
Do not produce all five items mechanically. Match the response to the question: a simple "should Claude Code or Codex handle this?" deserves a direct answer, not a framework dump.
data-ai
--- name: disk-cleanup description: Scan and clean macOS caches, package-manager data, crash dumps, and app caches to reclaim disk space. Deterministic — a config registry (targets.json) plus two scripts (survey.py read-only, clean.py executor) do all the measuring and deleting; the agent only relays a compressed summary and makes the few human-judgment calls. IMPORTANT — use this skill whenever the user's request on macOS involves: freeing disk space, cleaning/clearing caches, "disk is full", "
development
Generate and edit images using Google's Gemini image generation models (Nano Banana family). Supports style presets, platform-specific sizing (YouTube/slides/blog), variants, image editing via inlineData, reference images for style transfer, and organized output with metadata. Default model is Nano Banana 2 (gemini-3.1-flash-image-preview). Key is auto-decrypted via SOPS.
development
--- name: agency-docs-updater description: End-to-end pipeline for publishing Claude Code lab meetings. Accepts optional args: date (YYYYMMDD, "yesterday", "today") and lab number (e.g. "04"). Examples: "yesterday 04", "20260420 05", "04" (today, lab 04), "" (today, auto-detect lab). --- # Agency Docs Updater Execute ALL steps automatically in sequence. Only pause if a step fails and cannot be recovered. Read `references/learnings.md` before starting for known pitfalls. **Configuration**: pat
tools
This skill should be used when applying proper typography to prose text or files in Russian, English, German, or French — smart quotes per locale («ёлочки», “curly”, „Gänsefüßchen“, « guillemets »), correct dashes (тире, em/en dash, Gedankenstrich, tiret), non-breaking spaces, ranges, ellipsis, and French espaces insécables before ! ? ; :. Fully deterministic via a pinned typograf-based CLI; never apply these rules by hand. Triggers on "типографика", "typograf", "оттипографь", "smart quotes", "fix typography", "неразрывные пробелы".