通过复用已发布的设计系统组件、变量和样式,在 Figma 中新建或更新整页屏幕。
智能体与编排
define-goal
在代理开始工作前,把模糊意图转化为可量化、有验证依据的目标。
它能做什么
把用户意图改写成具体目标:明确产出物、验证方式、范围边界与停止条件。对模糊目标补充量化阈值;只在缺失信息会改变结果时追问一个问题。先调用 get_goal 检查是否已有进行中的目标,避免重复创建;仅在目标通过质量门槛后才调用 create_goal。范围限定在目标定义本身,不管理快照、决策日志或长期执行产物。
什么时候用它
- 为性能缺陷设定可验证的成功指标
- 为 PR 评论清理写出可校验的目标
- 把“调研一下”转化为带证据标准的研究目标
- 判断已有目标应替换、完成还是另开分支
技能文档
Define Goal
Overview
Shape the user's intent into an objective an agent can pursue honestly. Prefer measurable outcomes, explicit evidence, and bounded scope over activity descriptions.
This skill covers goal definition and goal-tool creation only. Do not create intermediate planning artifacts, durable snapshots, ledgers, decision logs, or resume files from this skill.
Workflow
-
Confirm that goal definition is actually needed.
- Use this skill when the user asks for
$define-goal, asks to create or set a goal, asks for the goal tool, or wants help turning an intention into a clear objective. - If the user only asks for ordinary implementation work, do the work directly instead of forcing goal creation.
- Use this skill when the user asks for
-
Restate the likely goal in concrete terms. A usable goal names:
- the specific outcome that will be true
- the main artifact, system, repo, environment, or user-facing behavior involved
- how completion will be verified
- what is in scope
- what is out of scope when ambiguity would matter
- the stop condition for asking the user instead of grinding
-
Make it quantitative when the domain supports it. Prefer numbers that represent real success, not decorative precision:
- pass/fail validators: exact tests, checks, CI jobs, evals, commands, or acceptance criteria
- quality thresholds: latency, error rate, cost, accuracy, recall, precision, coverage, flake rate, bundle size, memory, uptime, completion rate, or manual review criteria
- artifact constraints: file paths, affected modules, allowed commands, output formats, target environments, deadlines, or maximum blast radius
- evidence counts: number of reproduced failures, successful reruns, reviewed examples, migrated records, addressed comments, or verified cases
-
Repair weak goals before setting them.
- Rewrite vague goals into measurable objectives when local context makes the rewrite safe.
- Ask one concise clarification question when the missing detail changes the intended outcome or validation.
- Reject pure activity goals such as "make progress," "keep investigating," "improve things," or "work on X" unless they are sharpened into a verifiable outcome.
-
Check active goal state before creating a goal.
- Call
get_goal. - If there is no active goal and the objective meets the quality bar, call
create_goal. - If there is an active goal that still matches the user's intent, continue using it instead of creating a duplicate.
- If there is an active goal that conflicts with the new request, ask whether to finish the current goal, mark it complete if done, or start a separate goal-backed thread.
- Call
-
Create the goal only after it passes the quality bar.
- Use a single concise objective string.
- Include the verification evidence in the objective itself.
- Include scope bounds when they constrain the work.
- Include a token budget only when the user explicitly requested one.
- Do not call
create_goalfor an ordinary multi-step task unless the user explicitly asked for goal-backed work.
Goal Quality Bar
Before create_goal, the objective should answer:
- What concrete thing will be true when this is done?
- What evidence will prove it?
- What quantitative or binary threshold defines success?
- What scope boundaries matter?
- What should cause the agent to stop and ask?
Good:
Reduce checkout API p95 latency below 250 ms for the documented slow path by making the smallest safe server-side change, then verify with
npm run test:checkoutand the existing local latency benchmark showing p95 under 250 ms across 3 consecutive runs.
Good:
Resolve the open review comments on PR 123 that request code changes, update only the affected auth files and tests, and verify with the targeted auth test command plus
gh pr view 123showing no unresolved change-request threads.
Weak:
Make checkout faster.
Weak:
Keep investigating the PR comments.
Quantification Heuristics
- For bugs, define success as reproduction first, fix second, and a failing-then-passing validator when possible.
- For tests, name the exact command and required pass condition.
- For performance, name the metric, target threshold, measurement method, and number of runs.
- For quality work, define an observable acceptance bar such as reviewed examples, lint/typecheck/test pass, or user-approved artifact.
- For research, define the decision the research must enable, the sources or systems in scope, and the evidence standard.
- For operations, define healthy state, monitoring window, failure threshold, and rollback or escalation trigger.
Clarifying Questions
Ask only when a reasonable rewrite would risk pursuing the wrong outcome. Keep the question short and oriented around the missing validator or scope boundary.
Useful question shapes:
- "What metric should define success here: latency, cost, accuracy, or user-visible behavior?"
- "Which environment should I verify against: local, staging, or production?"
- "What is the minimum evidence you want before I mark this goal complete?"
If the user cannot provide a metric, propose the most honest binary validator available and ask for confirmation.
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