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- JPeetz/agent-skills
- 최근 소스 활동
- 2026년 8월 31일 06:31
- 감지된 SKILL.md 언어
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- 스타
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/JPeetz/agent-skills --skill model-routing-cost-optimizer명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
| name | model-routing-cost-optimizer |
| description | Use when routing tasks to the cheapest fitting model tier. |
| version | 1.0.0 |
| license | MIT |
| author | Skill Foundry |
| platforms | ["linux","macos"] |
| metadata | {"tags":["model-routing","cost-optimization","model-tiering","llm-cost","subagent-routing","provider-agnostic"],"complexity_level":"intermediate","similar_skills":["model-hierarchy"],"related_workflows":["classify_task_complexity","select_cost_appropriate_model","avoid_routing_anti_patterns"]} |
Route every agent task to the cheapest model that can still do it well. This skill
establishes a three-tier model hierarchy (cheap / mid / premium), a task classifier
that buckets work into ROUTINE / MODERATE / COMPLEX, and the decision rules that
turn a description into a model pick. It does not enforce any one provider — the
tier prices live in references/model-pricing.md so the body stays provider-
neutral — and it does not cover local quantized inference.
The core belief is blunt: most agent work is routine, and routing routine work to a premium model is pure waste. Down-tier by default; escalate on evidence, never on habit.
Use this skill when you want to:
Don't use for: fine-tuning a model, model evaluation or benchmarking, serving infrastructure (vLLM / TGI), or any task where correctness risk is high and you need the best possible reasoning regardless of price. If the work is irrecoverable or safety-critical, stop tiering and use the premium model.
model config of OpenClaw / Claude Code / Codex).references/model-pricing.md is illustrative, so refresh it against provider
docs before relying on a number.scripts/classify_task.py is stdlib-only.debug, architect,
design, security, adversarial, ambiguous push to Tier 3. Routine words
like read, fetch, check, format, status, list push to Tier 1.| Bucket | Heuristic | Typical Examples |
|---|---|---|
| ROUTINE → Tier 1 | Single-step, deterministic, no judgment | file I/O, heartbeat, status check, lookup, formatting, URL fetch |
| MODERATE → Tier 2 | Multi-step but well-scoped | code-gen on known patterns, summarization, draft writing, data transforms |
| COMPLEX → Tier 3 | Ambiguous, multi-approach, high-stakes | multi-step debugging, architecture, security review, long-context reasoning |
| Concern | Move |
|---|---|
| Task is routine | Tier 1 |
| Task is moderate | Tier 2 |
| Task needs image / vision | vision-capable model (never a text-only tier-1) |
| Task already failed on cheap | move up (escalation), never down |
| Heartbeat / cron / monitoring | always Tier 1 |
| Sub-agent spawn | default Tier 1 unless clearly moderate+ |
Each step ends with a checkable completion criterion.
State the task. Write the task in one line, including whether it needs images and whether a cheaper model already tried. Completion: you have a task statement with its vision and prior-failure flags.
Classify. Run python3 scripts/classify_task.py "<task>" in the terminal,
or read the bucket heuristics above by hand.
Completion: you have a label of ROUTINE, MODERATE, or COMPLEX.
Apply the vision override. If the task is vision-requiring, restrict the model choice to vision-capable options, ignoring any text-only option entirely — a text-only model cannot take image input at any price. Completion: the chosen model can actually accept image input.
Apply escalation and signal overrides. If a prior failure exists, go one tier up from the classifier result. If explicit complex signals appear, go to Tier 3. Completion: the final tier is never lower than the classifier would have produced.
Name a concrete model. From the provider's resolvable list, pick the cheapest model of the final tier that meets that tier's bar. Completion: you can name a concrete model, or a route to find one.
Run the anti-pattern sweep. If this is a sub-agent, heartbeat, cron, file I/O, or routine batch, drop it to Tier 1 unless the classifier returned MODERATE or above. Completion: no heartbeat/cron work remains on a premium tier.
scripts/classify_task.py returns Tier 1 for a routine phrase,
Tier 2 for a moderate phrase, and Tier 3 for a complex phrase.references/model-pricing.md exists and contains the pricing table and the
"prices change, check provider docs" caveat.