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builderio/efficient-frontier

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.

v1.0LATEST
NewUpdated Sep 9, 2026

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."

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Overall Score

88/100

Grade

A

Excellent

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

90

Quality

85

Clarity

90

Completeness

83

Summary

This skill teaches a frontier model orchestration pattern: reserve expensive frontier models for high-judgment decisions (architecture, prioritization, synthesis, final review) while delegating token-heavy, repeatable work (research, testing, mechanical edits) to cheaper subagents. It provides a structured workflow for spawning parallel subagents, writing self-contained handoff packets, and verifying delegated results before integration.

Detected Capabilities

Agent orchestration and spawningHandoff packet generationVerification command executionEvidence inspection and reviewCentral integration and synthesis

Trigger Keywords

Phrases that agents use to match this skill to user intent.

cost-optimize frontier modeldelegate to subagentsorchestrate parallel agentshandoff packetfrontiermodel delegationreduce token cost

Use Cases

  • Cost-optimize large projects by parallelizing research and implementation with subagents while keeping critical decisions with frontier model
  • Delegate repository scans, docs extraction, and source comparison to cheaper agents while frontier model evaluates findings
  • Distribute independent test runs, browser flows, log analysis, and failure clustering to parallel subagents for faster validation
  • Orchestrate multi-file refactors or bounded patches with clear ownership and central integration review
  • Parallelize debugging by sending separate agents to investigate independent theories while frontier model diagnoses root cause

Quality Notes

  • Clear workflow structure with five sequential steps
  • Well-defined handoff packet template with repo path, objective, scope, verification commands, and stop conditions
  • Explicit guardrails on delegation (no single-blocker delegation, no concurrent same-file edits, verification requirement)
  • Strong emphasis on evidence verification and central review before claiming completion
  • Practical common scenarios provided (research, coding, testing, debugging) with specific guidance
  • Good use of negative guidance (when to skip the pattern)
  • References `/efficient-fable` model but provides model-agnostic instructions
  • Default framing statement helps users apply the pattern consistently
Model: claude-haiku-4-5-20251001Analyzed: Sep 9, 2026

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