跳到正文
cccskills
免费在 GitHub 公开

efficient-frontier

Apply the same orchestration as `/efficient-fable` to any high-cost frontier model: delegate research, coding, and testing to cheaper subagents while keeping planning, synthesis, and final review with the expensive model.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(2)

  • SKILL.md3.3 KB
  • README.md2.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Efficient Frontier

Use the expensive frontier model where its marginal judgment matters. Push repeatable, bounded, or token-heavy work to cheaper/faster subagents.

Workflow

  1. Identify the frontier-only decisions: architecture, prioritization, ambiguity resolution, risk, synthesis, and final review.
  2. Identify delegable work: research scans, repository inventory, search, docs extraction, browser/testing passes, log reduction, test failure clustering, narrow coding, and mechanical edits.
  3. Spawn parallel subagents for independent slices with clear ownership, bounded scope, verification gates, and expected evidence.
  4. Require compact returns: findings, changed files, commands run, residual risk, stop conditions hit, and anything the frontier model must decide.
  5. Integrate and review centrally before presenting the result.

Handoff Packets

Write delegated prompts as self-contained packets. Assume the receiving agent has not seen the conversation. Include the repo path, objective, scope, out-of-scope areas, relevant files or search targets, expected return format, verification commands, and stop conditions.

Useful stop conditions:

  • The live code does not match the assumption in the handoff.
  • A verification command fails twice after a reasonable fix or retry.
  • The work appears to require files outside the assigned scope.
  • The agent cannot produce concrete evidence for its claim.

Review Loop

Treat delegated output as evidence to inspect, not a verdict to forward. Reopen important cited files, skim high-risk diffs, and rerun or spot-check the verification that matters before claiming completion. If delegated agents disagree, resolve the disagreement at the frontier-model layer.

Common Scenarios

Use these as soft suggestions:

  • Research: delegate broad repo scans, docs extraction, and source comparison; the frontier model keeps the judgment about what matters.
  • Coding: delegate bounded patches, refactors, or mechanical edits when file ownership is clear; integrate and review centrally.
  • Testing: let the frontier model choose the validation strategy and scripts, then use cheaper agents to run unit checks, browser flows, screenshots, and log reduction. Ask them to return exact commands, failures, likely causes, and whether the signal looks flaky, environmental, or product-relevant.
  • Debugging: send independent agents after separate theories, logs, or repro paths; keep the final diagnosis with the frontier model.

Guardrails

  • Do not delegate the immediate blocker if your next step depends on it.
  • Do not ask multiple agents to edit the same files at the same time.
  • Do not trust subagent conclusions blindly when the risk is high; inspect the important evidence yourself.
  • Do not claim universal savings. The pattern works best when exploration and implementation, testing, or research can be parallelized.

Default Framing

"I will use the frontier model as the orchestrator and reviewer, and use cheaper subagents for token-heavy research, coding, or testing so the expensive tokens go to judgment, synthesis, and final quality."

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Use in the BuilderIO/skills repo whenever adding, updating, publishing, documenting, validating, or wiring a public skill. Covers the repo-local skill files, root catalog docs, plugin metadata, @agent-native/skills dynamic install path, optional managed AGENTS/CLAUDE instruction blocks in ../agent-native/framework, and generated/synced Plan skill gotchas.

中文简介正在准备中。当前显示原文说明。

BuilderIO/skills45992026年10月15日 更新

Use when asked to watch, babysit, audit, review, compare, or fix another agent's work from a Codex session ID, Claude Code session/transcript, chat/thread link, PR, branch, log, or pasted run summary. Monitor until the other agent is done or blocked, reconstruct what the user asked, independently investigate the same problem to form your own hypotheses and approach, inspect what the agent actually changed and verified, compare the two investigations, report gaps and add-on directions, and optionally make scoped fixes when the user authorizes repair.

中文简介正在准备中。当前显示原文说明。

BuilderIO/skills45992026年10月15日 更新

an

免费

Open and operate Agent-Native workspace apps through Dispatch MCP, with inline app surfaces, browser-session authentication, and current screen state.

中文简介正在准备中。当前显示原文说明。

BuilderIO/skills45992026年10月15日 更新

Use when running Claude Fable on codebase-heavy or token-heavy work and the user wants Fable to orchestrate research, coding, and testing while cheaper subagents do bounded heavy lifting.

中文简介正在准备中。当前显示原文说明。

BuilderIO/skills45992026年10月15日 更新

factory

免费

Experimental workflow for configuring an autonomous software delivery factory. Use when choosing feedback sources, schedules, worktree behavior, autonomy gates, or host automations.

中文简介正在准备中。当前显示原文说明。

BuilderIO/skills45992026年10月15日 更新

Experimental workflow for babysitting one explicitly authorized pull or merge request. Use to monitor its live review state and checks, fix actionable in-scope findings, and apply separate reply, approval, merge, and soak gates.

中文简介正在准备中。当前显示原文说明。

BuilderIO/skills45992026年10月15日 更新

查看 BuilderIO 的全部技能

报告此技能的问题