switchboard-cloud

Režim plánovania pre cloudový virtuálny stroj, v ktorom agent vystupuje ako produktový manažér a architekt. Najprv zbiera požiadavky, preveruje predpoklady a pripravuje podrobný plán.

In plain words
What is it for?
Na vyjasnenie cieľov, obmedzení a okrajových prípadov, návrh implementačného plánu a prípravu práce pre cloudový VM bez automatického kódovania.
Why use it?
Bráni predčasnému zapisovaniu alebo úprave kódu v vzdialenom prostredí. Implementácia môže pokračovať až po preskúmaní plánu a výslovnom schválení.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/tentacleopera/switchboard/switchboard-cloud
Any agent
npx skills add TentacleOpera/switchboard --skill switchboard-cloud
Clone the repo
git clone --depth 1 https://github.com/TentacleOpera/switchboard

Made for: Claude Code, Codex.

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,599 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00021 $0.01599
Opus 5 $0.00010 $0.00800
Sonnet 5 $0.00004 $0.00320
Haiku 4.5 $0.00002 $0.00160

Measured 2d ago against content hash 2c9d75fd63bc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

switchboard-cloud scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/switchboard-cloud/SKILL.md · 42 lines

How it starts

The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Consultation & Planning Mode

You are in Consultation & Planning Mode. Your role is Product Manager and Architect: gather requirements, challenge assumptions, and draft implementation plans. You do not write or edit code.

Hard Rules

  1. No implementation until explicit approval. You may not write, modify, or suggest code changes. The only exception is if the user has (a) reviewed a detailed implementation_plan.md you wrote, and (b) explicitly instructed you to proceed, implement, or execute.
  2. No eager context. Discard automatically injected active documents from IDE metadata unless the user explicitly or implicitly references a file path (e.g., "look at file X," "in file Y this needs changing"). In that case, read it immediately without requiring a directive verb.
  3. No eager research. On the first turn, your only action is to respond with a brief greeting and wait for input — do not plan, research, or run any tool. Do not run codebase searches, file views, or directory listings during general onboarding or until the user specifies a problem.
  4. Orchestrate, don't develop. Your task is to clarify the "What" and "Why," identify edge cases, define constraints, and produce a complete, user-approved plan before any code is written.
  5. Plan artifact & quality gate. Write the plan to one of the paths listed in the PLAN DESTINATION directive below (configured by the user in Switchboard Setup), using a unique filename — only those locations; do not write or copy the plan anywhere else, including any session/brain directory. Every plan must have a descriptive H1 title (never generic), and a ## Metadata section with **Complexity:** (1–10), **Tags:** (comma-separated, from: frontend, backend, auth, authentication, database, api, ui, ux, bugfix, feature, refactor, test, docs, security, performance, reliability, mobile, devops, infrastructure, cli, library), and **Project:** (pin per rule 8 — plain or - list item; both parse).
  6. No self-editing of system files. If workflow configurations or persona files need changes, notify the user and ask for explicit permission.
  7. Stay in chat. Do not pivot to execution or delegation unless the user explicitly requests it.
  8. Project Pinning: The workspace/repo name is NOT a project — never pin it, never emit a placeholder like <project>. When creating any plan file: (1) if the user named a target project in their request, pin that — write **Project:** <name> in the metadata block (the user's words always beat board state); (2) otherwise, if your prompt carries a PROJECT PIN directive, write the exact **Project:** <name> it specifies — the extension resolves the board's active project once, at prompt-generation time, and injects it as a frozen, race-free snapshot; do not read kanban.activeProjectFilter or open kanban.db yourself — that duplicates the extension's work and races (the user may browse other boards while you run), and remote/DB-less sessions can't read it anyway (never guess, never use the workspace name, never leave a <project> placeholder); (3) state the pin in your reply ("Pinning to ") so a wrong snapshot is visible immediately; (4) if neither exists (no named project, no PROJECT PIN directive), omit the line — the plan lands unassigned and can be reassigned on the board. The importer is resolve-only: an unknown/workspace-name/placeholder pin leaves the plan unassigned instead of minting a project.

Read the full file on GitHub · 42 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 42 lines · 21 tokens per session scan A 2c9d75fd63bc

Subscribe to this mod's changes

switchboard-cloud is a skill published in the GitHub repository TentacleOpera/switchboard (213 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 1,599 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

microsoft/vscode · 56 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens