BuilderIO/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.

¿Qué es efficient-frontier?

efficient-frontier is a Claude Code agent skill that 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.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/BuilderIO/skills/tree/main/skills/efficient-frontier

Installed? Explore more Investigación y análisis de datos skills: obra/superpowers, affaan-m/quarkus-verification, affaan-m/uspto-database · View all 6 →

Preguntar en tu IA favorita

Abre un nuevo chat con esta habilidad de agente ya precargada.

Documentación

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."

Individual skills in this repo

This repo contains 10 individual skills — each has its own dedicated page.

BuilderIO/adding-a-skill

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.

BuilderIO/agent-watchdog

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, inspect what the agent actually changed and verified, report gaps, and optionally make scoped fixes when the user authorizes repair.

BuilderIO/efficient-fable

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.

BuilderIO/plan-arbiter

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.

BuilderIO/plow-ahead

Use when the user explicitly wants autonomous progress without routine clarification stops: "plow ahead", "do not stop", "use your best judgment", "keep going until done", "finish while I am away", "do not ask questions unless truly blocked", or similar. Convert ordinary ambiguity into stated assumptions, proceed through implementation and validation, stop only for true blockers, and end with a clear recap of decisions, changes, verification, and residual risk.

BuilderIO/quick-recap

Use when adding or following the red/yellow/green final status block convention for agent responses, especially by installing managed AGENTS.md or CLAUDE.md instructions.

BuilderIO/read-the-damn-docs

Use when implementing, integrating, upgrading, debugging, or answering anything involving third-party APIs, libraries, frameworks, CLIs, cloud services, model/provider SDKs, fast-moving product behavior, user requests for latest/current/official behavior, unfamiliar repo docs/specs, errors that may indicate API drift, or high-stakes auth, security, billing, data, migration, deployment, compliance, or privacy behavior. Forces Codex to web-search for current official docs and read primary docs before assuming from memory.

BuilderIO/stay-within-limits

Use when long-running or parallel agent work must respect 5-hour and weekly usage limits by checking usage between waves, pausing near the cap, and resuming only when the window is clear.

BuilderIO/visual-plan

Turn ordinary text plans into rich interactive visual plans with diagrams, file maps, annotated code, open questions, and UI/prototype review when useful.

BuilderIO/visual-recap

Turn a PR, branch, commit, or git diff into an interactive visual recap with diagrams, file maps, API/schema summaries, annotated diffs, and focused review notes.

Skills relacionados