Claude Opus 4.7: Effort Levels and Migration Prompt Template

One-sentence takeaway

Start Opus 4.7 at xhigh for coding and long-running Agent tasks, use high for most high-quality work, and spell out the objective, acceptance criteria, and verification steps; when migrating from 4.6, do not rely on the model to “fill in” missing requirements on its own.

Use cases

• Suitable tasks: Multistep coding, code review, repeated tool calls, long-running Agent sessions, and complex tasks that require self-checking.

• Unsuitable tasks: Simple classification, short question answering, and high-throughput, low-latency tasks; evaluate low/medium first for these tasks.

• Applicable model version: claude-opus-4-7.

• Applicable client, Agent, or API: Claude API, Claude Code, and Anthropic platforms that support effort.

• Recommended reasoning levels and parameters: Start coding/Agent tasks at xhigh; use at least high for general intelligence-sensitive tasks; use medium when cost-sensitive; use max only when your own evals prove it provides a gain. For xhigh/max, provide ample max_tokens; the official documentation suggests starting from 64K and tuning from there.

Ready-to-use content

The following is a reusable template assembled from Anthropic's official effort and migration guidance (it is not a complete system prompt published verbatim by Anthropic). Replace the angle-bracket fields with the actual task:

You are an implementation Agent responsible for delivery.

Goal: <describe the final, verifiable result in one sentence>
Context: <repository, input files, existing implementation, and relevant constraints>
Hard constraints: <interfaces, files, dependencies, permissions, or time limits that must not be changed>
Acceptance criteria:
1. <observable functional result>
2. <tests or checks that must pass>
3. <output/file format requirements>

First inspect the current state and choose the smallest viable approach, then execute the task. Before finishing, run each acceptance criterion;
if a tool fails, data is missing, or an assumption is uncertain, state it clearly and fix it or request additional information,
and do not substitute a plausible-looking placeholder for verification. Finally report: changes, verification commands, results, and unresolved risks.

This task involves multistep reasoning. Think carefully before responding.

When using the API, set output_config.effort per request (for example, "xhigh"); if the same long session depends on prompt caching, the official recommendation is not to change effort midway through the cached prefix.

Testing/workflow steps

1. Run the same set of representative tasks separately at high and xhigh, and record success rate, number of tool calls, tokens, latency, and amount of manual rework.

2. Run the prompts from the 4.6 era unchanged, and label behavioral differences where the “new model strictly follows” what the “old model omitted.”

3. Complete the goal, hard constraints, acceptance criteria, and failure handling in the template, then repeat the same tasks.

4. For code Agents, retain a worktree snapshot, test logs, and the final diff; do not judge completion solely from the model's self-report.

5. If the quality gain from xhigh does not cover its cost, step down to high/medium; do not use max as the default fallback.

Original evidence and data

• Anthropic's effort documentation: Opus 4.7 API defaults to high; for coding and Agent use cases, start at xhigh; high is the minimum starting point for most intelligence-sensitive work; medium is for saving cost; reserve max for genuinely frontier problems.

• Official release page: Opus 4.7's xhigh sits between high and max; Claude Code's default has been raised to xhigh; public beta task budgets can guide token use for long-running tasks.

• The official documentation also says that Opus 4.7 follows effort more strictly than 4.6, especially at low/medium; if a complex task is too shallow at a lower level, increase effort instead of using prompts to work around the model's behavior.

• When migrating from 4.6, Anthropic reports that the new tokenizer may map the same input to approximately 1.0–1.35× as many tokens, and that subsequent Agent turns at higher levels may think more; measure cost on real traffic.

Scope and limitations

• The template above is a combined template based on official principles, not Anthropic's complete official prompt; it needs to be adapted to the product and tool schema.

• Effort controls token usage for the entire response, including tool calls and thinking (when enabled); it is not a control for visible answer length. Add a separate length requirement when shorter output is needed.

• max may provide only a small quality gain on most workloads while significantly increasing cost; decide based on your own evals.

• After 4.7 became more “literal” in its execution, implicit constraints in old prompts that relied on the model to fill them in on its own may no longer work.

Source excerpt or observation (short compliant quotation only)

The official effort recommendation is “Start with xhigh for coding and agentic use cases”; the release page also warns that old prompts and harnesses should be retuned because the new model follows instructions more strictly.