pick-model-effort
Skill5 starsChanged 21 days agoMITView on GitHub
Choose the Claude model and effort level for a task or a subagent, so cheap work runs on cheap models and hard work gets the strong ones. Use before spawning subagents or parallel agents, when planning a multi-step task, when asked "which model should I use", or when setting up agents in .claude/agents.
In this repository5 other files it gives its agents.
- commit-messageSkill
- explain-codeSkill
- release-notesSkill
- safe-migrationSkill
- write-claude-mdSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 3 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 24
When unsure, go higher for decisions and lower for mechanical work.
- Very specific: line 28
Use only models your account offers.
- Very specific: line 54
If you need a different setting for one call, pass model (and effort, where your version supports it) on that call instead of editing the …
- Very specific: line 56
If an agent isn't installed (for example, the skill was copied without the agents), pass model on each Agent call using the table in step 1.
- Distinctive: line 62
Run independent lookups in parallel, on the cheap model.
- Distinctive: line 63
Don't give a subagent a decision it can't see the context for.
- Very specific: line 67
If the next task is unrelated to the last one, suggest /clear or a new session.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Pick the model and effort
The goal is accurate work without paying top-model prices for searching files. Pick the settings yourself, say what you picked when you delegate, and move on.
1. Sort the work
Split the task into pieces and give each one a class:
| Class | Examples | Model | Effort |
| Lookup | find files, grep, read docs, list callers, summarize logs, classify, reformat | haiku | low |
| Routine build | clear-scope edits, tests from a spec, renames, small features, docs | sonnet | medium |
| Judgment | code review, bug hunting, hard debugging, security, migrations | opus | high |
| Design | architecture, plans, research with trade-offs, decisions that are costly to undo | opus | xhigh |
| Hardest | long autonomous runs, or a problem where opus already fell short | fable | high or xhigh |
Rules of thumb:
- When unsure, go higher for decisions and lower for mechanical work.
- A stronger model at lower effort usually beats a weaker model at high effort.
maxeffort only when being right matters far more than cost or time.- Lookups are where most tokens go. Moving them off the main model is the biggest saving.
- Use only models your account offers. If
fableisn't available, useopusat xhigh.
2. Know how Claude Code picks a subagent's model
First match wins:
modelpassed for that one call (the Agent tool'smodelparameter)model:in the agent file (inheritmeans the main session's model)- The
CLAUDE_CODE_SUBAGENT_MODELenvironment variable - The main session's model
Effort comes from effort: in the agent file or the call. The CLAUDE_CODE_EFFORT_LEVEL environment variable overrides both.
The trap: the built-in Explore, Plan and general-purpose agents inherit the main model. Six parallel Explore agents in an Opus session are six Opus agents. Pass model: "haiku" when you spawn them for lookups, or use the searcher agent below.
3. Use the agents in this kit
This kit installs four agents with sensible defaults:
| Agent | Model, effort | Tools | Use for |
searcher | haiku, low | read-only | finding code, lookups, reading many files and returning a short summary |
implementer | sonnet, medium | all | routine edits and tests with a clear spec |
reviewer | opus, high | read-only | reviewing a diff, hunting bugs, checking a plan |
architect | opus, xhigh | read-only | design, plans, trade-offs |
If you need a different setting for one call, pass model (and effort, where your version supports it) on that call instead of editing the agent.
If an agent isn't installed (for example, the skill was copied without the agents), pass model on each Agent call using the table in step 1.
4. When you delegate
- In one line, say which agent or model and effort you chose and why, for example: "Searching with
searcher(haiku), thenreviewer(opus, high) on the diff." - Send heavy reading to a subagent and ask for a short summary with file paths, not a dump. That keeps the main context small, which saves tokens on every later turn.
- Run independent lookups in parallel, on the cheap model.
- Don't give a subagent a decision it can't see the context for. Keep the decision in the main session and delegate the gathering.
5. Keep the main session cheap
- If the next task is unrelated to the last one, suggest
/clearor a new session. A long context makes every turn cost more. - If the user asks for something that breaks these rules (an Opus or Fable subagent at high effort for a file search, say), point it out in one line with the cheaper option, then do what they decide. Don't block them or repeat the point.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

