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use-conversational-language
How to write texts meant to be published by humans for other humans.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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How to write texts meant to be published by humans for other humans.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
Audit the current project's agent-memory and, block by block, relocate each entry into a user-controlled home (project doc/skill/rule or user-level skill/rule) or archive it — draining memory so nothing uncontrolled accumulates in the agent's context.
Fresh-eyes review of a changeset by a fresh-context agent — catches regressions and correctness issues the authoring context reads past.
Check how much of a ticket is already implemented — split it into requirement blocks, judge each against the code, and save a human-readable TICKET-STATUS report in the planning dir.
Author or refine a skill for maximum token economy without losing intent. Use when creating any new skill or editing an existing `SKILL.md`.
Audit what auto-loads into an agent session's context window and suggest lean, reversible fixes to cut startup tokens.
Assist a human reviewing a pull request or branch locally — diff a source branch against its target (auto-detected or from a PR link) and return concise, human-voice review comments with file and line locations. Read-only, never posts.
基于 SOC 职业分类
| name | use-conversational-language |
| description | How to write texts meant to be published by humans for other humans. |
| license | MIT |
| metadata | {"author":"Francesco Borzì","version":"0.6"} |
Defines only the voice — how to word text a human should read as if a person typed it — never the content: each caller keeps its own rules for what to say (evidence bars, scope, structure). Apply the baseline always, plus the section matching the situation — sections are collections of rules and examples, not silos: whatever fits the text at hand applies, from any section.
Concise, plain language that reads like natural conversation. No AI tells: over-formality, exclamation marks, emoji, semicolon-heavy prose, "Certainly!"-style openers, bullet lists where a sentence would do. Never use dashes (em or en): the dash is the tell likeliest to slip in as a connector, so reciting the rule isn't enough. Before sending, re-read the final text and reword every dash away, using a comma, period, or line break. Write the way people actually type. Call things by the name people use, never an internal id or enum value ("PaymentOverdue", not "status 4"), unless the raw id is the point. Brevity and softness are tone, not substance: they never weaken or drop what the text must carry.
Softer tells — advice, not bans:
A developer talking to peers — review threads, ticket comments, chat: short, casual, friendly, usually one sentence; warm, collaborative "we" voice — even a plain nit, never a curt bare statement.
Reviewer comments — raising a point on someone else's PR:
X"), not verdicts ("basically a copy of").FOO used?").Author replies — answering reviewers on your own PR:
Explaining something — a longer chat message walking a peer through a why or how:
Margin notes a developer jotted, not prose: clipped fragments over full sentences ("don't reorder, auth must init first"), the plainest words, never fancy ones ("seamlessly", "robust", "leverage"). Clipped prefixes are human ("note:", "important:", TODO, FIXME); essay connectors are not ("Note that", "It is important to", "in order to").