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benchmark-to-brief基准简报

Agent Skill

benchmark-to-brief 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

470

周安装

19

GitHub Stars

公开资料未说明

下载量

147
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:benchmark-to-brief(基准简报)
来源仓库:https://github.com/postplusai/postplus-skills
仓库路径:skills/benchmark-to-brief
安装命令:
npx skills add https://github.com/postplusai/postplus-skills --skill benchmark-to-brief
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/postplusai/postplus-skills --skill benchmark-to-brief

简介

benchmark-to-brief 将已验证的研究结果转化为可执行的规划输入,如 campaign briefs 或 test matrices。

  • 适用于策略与创意交接层,连接研究与执行,产出变量控制计划或 hook families。
  • 必须基于已存在的研究事实,不能用于 greenfield 头脑风暴。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Benchmark To Brief

Follow shared release-shell rules in:

  • postplus-shared release-shell rules

Use this skill after research already exists.

This skill is the strategy and creative handoff layer between research and execution. It should consume validated findings and turn them into usable planning inputs before copywriting, production, outreach, or publishing moves forward.

This skill is for converting structured evidence into:

  • campaign briefs
  • concept candidates
  • hook families
  • test matrices
  • variable-control plans

It is not for greenfield brainstorming.

Fact Rule

Everything produced by this skill must be grounded in available evidence.

Allowed evidence sources include:

  • benchmark reports
  • master tables
  • pattern tables
  • strategy tables
  • comment analyses
  • validated performance data

Do not invent:

  • target personas with no source basis
  • hooks that contradict benchmark wording
  • unsupported product claims
  • audience motivations not reflected in data

If the evidence is incomplete, say so explicitly and separate:

  • Observed from sources
  • Inference
  • Open question

Default Workflow

1. Load the smallest sufficient evidence set

Prefer the most structured sources first:

  1. final report
  2. strategy table
  3. pattern table
  4. video master table
  5. comment summaries

Do not read everything by default if the answer is already supported.

Source Selection Rule

Prefer the smallest sufficient evidence set already present in the active project. If the current task clearly belongs to one client or project folder, start there. Do not assume one client folder is the global default for all future work.

When the master table contains shot-level fields, treat them as a stronger source than your own rewrite instincts:

  • videoOpeningLineExact
  • videoClosingLineApprox
  • videoShotTimeline
  • videoSpokenAudioFlow

Those fields should guide the opening shell, information order, pacing, and closing style of any derived concept or script brief.

2. Extract facts before proposing

Always extract:

  • winning lanes
  • repeated hook shells
  • repeated structure types
  • visual format tendencies
  • repeated user-language patterns
  • strong benchmark examples

Before writing concepts, write down what is actually true.

3. Map facts to brief fields

For each concept or brief recommendation, tie it back to:

  • source artifact
  • relevant benchmark ids or examples
  • reason this pattern fits the product

Each concept should answer:

  • what problem is being cut
  • what hook shell is being reused
  • what content lane it belongs to
  • what variable is being tested
  • which research evidence supports it

4. Keep concept scope narrow

Do not generate vague ideas like:

  • "make a productivity video"
  • "do a relatable AI ad"

Prefer:

  • one problem
  • one hook family
  • one format
  • one test variable

5. Preserve benchmark language

When adapting hooks, preserve the source shell whenever possible.

Do not "improve" benchmark phrasing unless the user asks for a variant test.

Good adaptation:

  • benchmark: Here is a Gmail trick I guarantee you didn't know.
  • adapted: Here is a Gmail reply shortcut I guarantee you didn't know.

Bad adaptation:

  • rewriting into abstract brand language
  • replacing concrete pain with generic value claims

Output Shapes

Common outputs for this skill:

  • campaign brief
  • 10 concept candidates
  • hook library
  • lane prioritization
  • AB test matrix

These outputs should be treated as execution inputs, not end-user proof that the underlying research happened. If the upstream research is still fuzzy, thin, or contradictory, stop and surface that gap before turning it into a brief.

Campaign Brief

Include:

  • objective
  • priority lanes
  • persona constraints if supported by data
  • approved hook families
  • prohibited directions
  • variables to test
  • source basis

Concept Candidate

Each concept should include:

  • conceptId
  • problemToCut
  • hookType
  • hookDraft
  • targetLane
  • formatType
  • whyThisFits
  • sourceBasis
  • testVariable

Source Basis Requirement

Every concept list should include a sourceBasis section.

Example:

  • final report says workflow is the top-priority lane
  • final report says high-value language includes Stop switching tabs
  • pattern table shows gmail_fix_or_hidden_setting is high fit
  • master table contains strong Gmail pain/tutorial examples

If you cannot cite source basis, do not present the idea as recommended.

Downstream Handoff Rule

This skill should usually hand off to one of these next layers:

  • script, concept, or production planning
  • asset generation workflows
  • content packaging workflows
  • outreach or publishing only when the content has already been turned into approved execution-ready material

Do not hand raw research directly into publishing from this skill. First make the execution object explicit: brief, concept list, hook set, script, or approved copy.

Project-Specific Guidance(if user specificly state a project preference when using this skills, wirting down and memory it)

Failure Mode

Stop and state the gap if:

  • the available data is too thin
  • strong benchmarks do not exist for the requested direction
  • the user asks for a claim the evidence does not support

Then offer:

  • the closest evidence-backed option
  • what additional research would be needed

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

39.58%
按下载量换算58

Claude

30.91%
按下载量换算45

Cursor

17.11%
按下载量换算25

Gemini CLI

10.14%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/postplusai/postplus-skills --skill benchmark-to-brief 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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