If you’ve run long agentic sessions in Claude Code, you’ve probably hit this: the agent wraps up, reports success, and something is still broken. The model didn’t lie — it genuinely assessed its work as complete. But it was wrong.

Claude Code v2.1.139 (shipped May 12, 2026) addresses this with the /goal command, a feature that separates the model doing the work from the model judging whether that work is done. This guide explains how it works and how to write goals that actually catch incomplete work.

Source note: This guide is based on the official Claude Code documentation at code.claude.com/docs/en/goal, cross-verified with VentureBeat and ExplainX. For the most current syntax, always refer to the official docs — Claude Code is under active development and command syntax may change.

How /goal Works

When you set a goal with /goal, two separate processes run during your session:

  1. The worker — the main Claude model (typically Sonnet 4.6 or Opus) that executes your task, writes code, runs tools, and does the actual work.

  2. The evaluator — a separate Claude Haiku instance that, after every turn, reads what the worker produced and checks: Was the goal met?

The evaluator is structurally constrained: it cannot run tools. It only reads what the worker surfaced. This prevents the evaluator from getting creative about confirming success — it can only judge the evidence in front of it.

If the goal is met: the session ends cleanly and success is logged. If the goal is not met: the evaluator provides a specific reason back to the worker, which the worker uses in its next turn to correct course.

Setting a Goal: The Basics

Use /goal in your Claude Code session before starting work on a complex task. The exact command syntax — including any subcommands or options beyond the basic /goal invocation — is documented at code.claude.com/docs/en/goal. Refer there for the full up-to-date syntax rather than relying on any examples reproduced here.

The core principle is: your goal should be a verifiable condition, not a description of effort.

Writing Goals That Work

The evaluator is checking facts, not intentions. This makes goal quality critical.

Good goals are measurable

Weak: “The user authentication system should work correctly”
Strong: “All 23 tests in tests/auth/ pass with zero failures”

Weak: “The API endpoint should handle errors properly”
Strong: “A POST to /api/users with a missing email field returns HTTP 422 with an errors key in the response body”

Good goals reference checkable outputs

The evaluator reads what the worker surfaced: code files, terminal output, test results, assertions. Your goal should point to something the evaluator can actually inspect.

Checkable: file contents, test pass/fail output, specific return values, error messages
Not checkable by the evaluator alone: performance characteristics, subjective quality, “no regressions” without a specific test suite

Multiple conditions can be combined

According to the official documentation, goals can include multiple conditions. Structure them as a checklist when you need several things to be true simultaneously.

Using /goal in Non-Interactive Mode (claude -p)

The /goal command is particularly powerful in non-interactive pipelines where there’s no human in the loop to assess completion. When combined with claude -p (non-interactive mode), the evaluator becomes the only check on whether a long-running agent session actually achieved what it was supposed to.

For production pipelines, well-defined goals provide:

  • Auditability — you know exactly what condition was verified at session end
  • Retry clarity — when a goal fails, the evaluator’s reason is logged and can inform retry logic
  • Trust — downstream systems can treat a goal-satisfied session differently from one that ended ambiguously

Common Mistakes

1. Setting goals too late
Set your goal before the agent starts significant work, not after. Goals set mid-session may not have the context they need for accurate evaluation.

2. Mixing execution criteria with quality criteria
“The code is clean and well-commented” is not a goal the Haiku evaluator can reliably verify. “The function has a docstring and all variable names are more than two characters” is checkable.

3. Goals that only the worker can verify
If verifying the goal requires running the code, the evaluator can’t confirm it independently. Either have the worker run tests and surface the output explicitly, or frame the goal around the surfaced output rather than the execution itself.

Resources

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260515-0800

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