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goal-writer

Use when the user wants to write, refine, audit, or strengthen a Codex `/goal` prompt for long-running work, including debugging, optimization, flaky tests, migrations, refactors, research reproduction, experiment campaigns, and evidence-backed deliverables.

معلومات المصدر

المستودع
muxuuu/goal-writer
آخر نشاط في المصدر
١٨ مايو ٢٠٢٦ في ١٨:٣٢
لغة SKILL.md المكتشفة
الإنجليزية
النجوم
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التفرعات
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خيارات التثبيت

يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.

مراجعة ملفات المصدر

اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.

عرض SKILL.md

SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
goal-writer
description
Use when the user wants to write, refine, audit, or strengthen a Codex `/goal` prompt for long-running work, including debugging, optimization, flaky tests, migrations, refactors, research reproduction, experiment campaigns, and evidence-backed deliverables.
# Goal Writer Turn a rough task into a strong Codex `/goal` prompt. A strong Goal is a thread-scoped completion contract: it defines the target, the evidence that proves progress, the constraints, the working boundary, the iteration rule, and the blocked-stop report. ## Source Principles This skill follows the OpenAI Goals practice: - A Goal fits work with a durable objective, an evidence-based finish line, and a path that may need several turns. - Completion must be checked against concrete evidence: tests, benchmarks, logs, files, generated artifacts, command output, or research evidence. - The Goal should preserve uncertainty explicitly when exact proof may be unavailable. - A vague finish line should trigger clarification before drafting. - One-turn edits, simple explanations, short reviews, and single-answer questions should receive a normal prompt recommendation. ## Readiness Gate Before writing `/goal`, check whether the request has enough information. Required: - Outcome: what should be true when done. - Verification surface: what concrete evidence proves it. Important: - Constraints: behavior, APIs, quality bars, accuracy standards, or files that must stay intact. - Boundaries: allowed files, repositories, data, tools, commands, or external sources. - Blocked stop condition: when Codex should stop and what it should report. Ask one concise question when Outcome or Verification surface is absent. Ask one question per turn. Choose the highest-impact absent field. Stop asking once the Goal can be audited. Default question limit: 3. After 3 questions, either write the strongest defensible Goal from confirmed information or state the single absent item blocking a defensible Goal. ## Question Priority 1. Verification: what tests, benchmark, logs, artifact, report, or source material should decide completion? 2. Outcome: what exact state, behavior, threshold, or deliverable should exist at the end? 3. Constraints: what behavior, interface, result, data, or file must stay intact? 4. Boundaries: what files, folders, repositories, commands, data, tools, or sources may Codex use? 5. Blocked stop: what should the final report contain if completion stays blocked? ## Drafting Pattern Use this shape when ready: ```text /goal <desired end state>, verified by <specific evidence>, while preserving <constraints>. Use <allowed inputs, tools, files, data, or repositories>. Between iterations, <how Codex should choose and report the next best action>. If blocked or valid paths are exhausted, stop with <attempted paths, evidence gathered, blocker, and next input needed>. ``` Keep the final Goal compact. Prefer one recommended Goal. Add a strict version only when the user asks for tighter control or the task has high blast radius. For examples by task type, read `references/goal_patterns.md`. ## Output Format When more information is needed: ```markdown 需要先确认一个关键点:<one question> ``` When ready: ````markdown **推荐 Goal** ```text /goal ... ``` **审计点** - 结果: - 证据: - 约束: - 边界: - 迭代: - 阻塞: ```` For a one-turn task: ````markdown 这个任务适合普通 prompt: ```text ... ``` ```` ## Quality Bar - Preserve user-provided facts exactly. - Use only user-confirmed tests, commands, metrics, files, tools, or source material. - Ask before choosing verification evidence when the evidence surface is unclear. - For research, separate confirmed findings, approximate support, blocked claims, and remaining uncertainty. - For coding work, include regression protection and explicit verification commands when the user provides them. - For experiment campaigns, require a result ledger, run identifiers, metrics, and stop criteria.
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