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.
npx agentmods add skills/builderio/skills/efficient-frontiernpx skills add BuilderIO/skills --skill efficient-frontiergit clone --depth 1 https://github.com/BuilderIO/skillsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00047 | $0.00687 |
| Opus 5 | $0.00023 | $0.00344 |
| Sonnet 5 | $0.00009 | $0.00137 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
efficient-frontier 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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Efficient Frontier
Use the expensive frontier model where its marginal judgment matters. Push repeatable, bounded, or token-heavy work to cheaper/faster subagents.
Workflow
- Identify the frontier-only decisions: architecture, prioritization, ambiguity resolution, risk, synthesis, and final review.
- Identify delegable work: research scans, repository inventory, search, docs extraction, browser/testing passes, log reduction, test failure clustering, narrow coding, and mechanical edits.
- Spawn parallel subagents for independent slices with clear ownership, bounded scope, verification gates, and expected evidence.
- Require compact returns: findings, changed files, commands run, residual risk, stop conditions hit, and anything the frontier model must decide.
- 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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 77 lines · 47 tokens per session scan A d3bb746c5ec1
efficient-frontier is a skill published in the GitHub repository BuilderIO/skills (4,152 stars, last pushed 6d ago), licensed MIT. It adds 47 tokens to every session and 687 once invoked, about $0.0002 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.
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