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Agent Skill · 研究检索

bookforge-sem-performance-optimization(Bookforge SEM 性能优化)

bookforge-sem-performance-optimization 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

bookforge-sem-performance-optimization 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 37,004。

总安装 1,822周安装 73GitHub Stars 公开资料未说明下载 590核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:bookforge-sem-performance-optimization(Bookforge SEM 性能优化)
来源仓库:https://github.com/quochungto/bookforge-sem-performance-optimization
安装命令:
openclaw skills install bookforge-sem-performance-optimization
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install bookforge-sem-performance-optimization

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,适合在 OpenClaw 中快速定位候选结果。适用于优化搜索引擎营销绩效,使用点击率与转化费用公式过滤关键词。可结合来源仓库和原始 README 核验具体用法,辅助 SEM 策略调整。安装前需确认权限范围、维护状态,注意是否会触发联网、命令执行或文件读写。

建议在使用前评估技能的实际输出边界,避免依赖其直接决策。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install bookforge-sem-performance-optimization;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

bookforge-sem-performance-optimization 怎么安装?

在终端执行 openclaw skills install bookforge-sem-performance-optimization。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

bookforge-sem-performance-optimization 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

bookforge-sem-performance-optimization 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

bookforge-sem-performance-optimization 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

bookforge-sem-performance-optimization 用的人多吗?

公开数据是累计安装 1,822 次,近一周安装 73 次,下载 590 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

bookforge-sem-performance-optimization 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
bookforge-sem-performance-optimization

Bookforge SEM 性能优化 · 本页

1,822—调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
sem-performance-optimization
description
Optimize Search Engine Marketing performance using CTR, CPC, CPA formulas, Quality Score benchmarks, and keyword profitability filtering. Use whenever a founder or marketer is running Google Ads, Bing Ads, or any SEM campaign, measuring CAC on paid search, optimizing ad groups, pruning unprofitable keywords, improving Quality Score, testing SEM as a channel, or comparing SEM vs other acquisition channels. Activates on phrases like 'SEM', 'Google Ads', 'AdWords', 'PPC', 'pay-per-click', 'CPC', 'CPA', 'CTR', 'Quality Score', 'keyword optimization', 'paid search', 'ad groups', 'bid strategy', 'search advertising'.
version
1.0.0
homepage
https://github.com/bookforge-ai/bookforge-skills/tree/main/books/traction/skills/sem-performance-optimization
metadata
{"openclaw":{"emoji":"📚","homepage":"https://github.com/bookforge-ai/bookforge-skills"}}
status
draft
source-books
title
Traction: A Startup Guide to Getting Customers
authors
["Gabriel Weinberg", "Justin Mares"]
chapters
[10]
domain
startup-growth
tags
[startup-growth, sem, google-ads, paid-search, performance-marketing]
depends-on
[bullseye-channel-selection]
execution
tier
1
mode
hybrid
inputs
description
Product description, target keywords, current SEM metrics
tools-required
[Read, Write]
tools-optional
[AskUserQuestion]
mcps-required
[]
environment
Plain-text working directory for SEM analysis and optimization plans
discovery
goal
Optimize SEM performance using quantitative formulas and Quality Score benchmarks
tasks
audience
roles
[startup-founder, growth-marketer, ppc-specialist]
experience
beginner-to-intermediate
when_to_use
triggers
prerequisites
why
SEM should be selected via Bullseye against existing search demand
not_for
environment
codebase_required
false
codebase_helpful
false
works_offline
true
quality
scores
with_skill
null
baseline
null
delta
null
tested_at
null
eval_count
0
assertion_count
12
iterations_needed
0

SEM Performance Optimization

When to Use

The startup is running SEM and needs to improve performance, or is testing SEM as a new channel. Before starting, verify:

  • There is existing search demand for the category (SEM is demand fulfillment, not demand creation)
  • The user has or can access basic SEM metrics (spend, clicks, conversions)
  • The goal is CAC-positive customer acquisition, not brand awareness

Context & Input Gathering

Required Context (must have — ask if missing)

  • Current SEM metrics or test hypothesis: spend, clicks, conversions, CPA

→ Check prompt for: "spending X on ads", CTR numbers, CPC numbers → If missing, ask: "What are your current SEM metrics? Spend, clicks, conversions — even rough numbers."

  • Unit economics: CAC target and LTV

→ Check prompt for: "CAC should be X", "LTV is Y", "customer value" → If missing, ask: "What's your approximate customer LTV? And what CAC is acceptable?"

Observable Context

  • Keyword categories: category terms (fat-head) vs specific queries (long-tail)
  • Competitor SEM activity: how crowded the space is

Default Assumptions

  • Average AdWords CTR benchmark: 2.0%
  • Low Quality Score threshold: CTR < 1.5% (Google penalizes these)
  • Initial test budget: $250-$500 per keyword cluster
  • 3:1 LTV:CAC ratio minimum for sustainable channel

Sufficiency Threshold

SUFFICIENT: metrics + unit economics known
PROCEED WITH DEFAULTS: metrics known, use 3:1 LTV:CAC as heuristic
MUST ASK: no SEM metrics or hypothesis at all

Process

Use TodoWrite:

  • [ ] Step 1: Calculate current performance (CTR, CPC, CPA)
  • [ ] Step 2: Evaluate Quality Score against benchmarks
  • [ ] Step 3: Apply profitability filter (CPA vs LTV)
  • [ ] Step 4: Prune unprofitable keywords
  • [ ] Step 5: Expand to long-tail and restructure ad groups

Step 1: Calculate Current Performance

ACTION: For each ad group, calculate the three core SEM metrics:

  • CTR (Click-Through Rate) = clicks / impressions × 100
  • CPC (Cost Per Click) = spend / clicks
  • CPA (Cost Per Acquisition) = CPC / conversion_percentage, or spend / conversions

Worked example: 100 impressions, 3 clicks → CTR 3%. $1 CPC with 10% conversion → CPA = $1 / 0.10 = $10.

Write current metrics per ad group to sem-baseline.md.

WHY: Optimization without baseline metrics is guessing. The three formulas are the universal measurement framework — every SEM decision ultimately traces back to one of these numbers. Founders who skip the baseline and jump to "optimize my ads" produce random changes with random results.

Step 2: Evaluate Quality Score Against Benchmarks

ACTION: Check CTR against Google's Quality Score benchmarks:

  • Average CTR benchmark: 2.0% — this is the rough AdWords average
  • Low threshold: 1.5% — below this, Google assigns low Quality Score → worse ad placements AND higher CPC

For each ad group with CTR < 1.5%, flag it. You're in a Quality Score penalty spiral: low CTR → low Quality Score → higher CPC → worse ROI.

WHY: Quality Score is a multiplicative effect. An ad with CTR of 1% doesn't just get worse performance — Google charges more per click AND shows the ad less often. This is a doom loop that only gets worse unless fixed. The 1.5% threshold is where the penalty kicks in hard.

IF CTR is 1.5-2.0% → rewrite ad copy for relevance, use Dynamic Keyword Insertion. IF CTR is below 1.5% → consider pausing the ad group entirely while you rewrite.

Step 3: Apply Keyword Profitability Filter

ACTION: For each keyword, calculate: Is CPA less than LTV × profit margin?

Formula: profitable keyword = CPA < LTV_margin

Example: LTV = $300, 30% margin = $90 profit per customer. If CPA > $90, the keyword is losing money.

Keywords are profitable in three bands:

  • Highly profitable (CPA < 30% of LTV margin) — scale spend
  • Marginally profitable (CPA 30-100% of LTV margin) — optimize or maintain
  • Unprofitable (CPA > LTV margin) — pause or kill

WHY: Founders often compare CPA to product price, not to profit margin. At $99/month product price, a $95 CPA looks fine — until you remember you only make $30 profit per month and the customer churns in 8 months. True profitability needs margin and retention in the calculation, not just price.

IF you don't have retention data → assume 12-month average and adjust as data comes in.

Step 4: Prune Unprofitable Keywords

ACTION: Pause or delete unprofitable keywords identified in Step 3. Be ruthless — a portfolio of 100,000 keywords is not inherently better than 10,000 profitable ones.

Archives.com case study: started with 100,000 keywords, pruned to 50,000 profitable ones. The pruning itself improved average CPA by removing drag from unprofitable keywords that were consuming budget.

Write the pruning list to sem-pruning.md with reasons per keyword.

WHY: Unprofitable keywords consume budget that could go to profitable ones. Even if you don't scale spend, removing bad keywords redirects the same budget to good keywords, improving overall CPA. The pruning is often the fastest win in an SEM optimization project.

Step 5: Expand to Long-Tail and Restructure Ad Groups

ACTION: For profitable category keywords, expand to long-tail variants:

  • Category keyword: "project management software"
  • Long-tail variants: "project management software for construction", "cheap project management software", "project management software vs Asana"

Long-tail keywords are less competitive → lower CPC → often higher conversion (more specific intent).

Restructure ad groups by keyword cluster — each tight cluster gets its own ad group with relevant ad copy and landing page. Use Dynamic Keyword Insertion to personalize ads by query.

WHY: Broad ad groups mean one ad tries to match 50 different queries — Quality Score suffers because the ad isn't specific enough. Tight ad groups (5-10 related keywords) with custom ad copy produce dramatically higher CTR and lower CPC. This is the single biggest structural win in mature SEM accounts.

Inputs

  • Current SEM metrics (spend, clicks, conversions, per ad group)
  • Unit economics (LTV, margin)
  • Target keywords or existing keyword list

Outputs

Four markdown/data files:

  1. sem-baseline.md — CTR, CPC, CPA per ad group
  2. sem-quality-score-audit.md — Ad groups flagged by Quality Score threshold
  3. sem-pruning.md — Unprofitable keywords to pause with reasons
  4. sem-optimization-plan.md — Ad group restructure, long-tail expansion, A/B test queue

Key Principles

  • CTR below 1.5% is a doom loop. Fix or pause immediately. WHY: Google penalizes low Quality Score with higher CPC AND lower impressions. Letting a low-CTR ad group run is actively worse than pausing it.
  • Profitable keyword = CPA < LTV margin, not CPA < product price. WHY: Product price is revenue, not profit. Unit economics depend on margin and retention, not list price. Comparing CPA to price produces keywords that "look profitable" but lose money over the customer lifetime.
  • Prune aggressively. 10,000 profitable keywords beats 100,000 mixed. WHY: Unprofitable keywords consume the budget that could go to profitable ones. Pruning redirects spend without growing it.
  • Tight ad groups beat broad ad groups. 5-10 closely-related keywords per ad group with custom copy. WHY: Google's Quality Score rewards relevance. Broad ad groups where one ad tries to match 50 queries tank CTR and raise CPC.
  • Long-tail is where profit lives. Category terms are competitive and expensive. Long-tail is less competitive AND has higher intent. WHY: "Project management software" has 50 advertisers bidding; "construction project management software for contractors" has 3. Lower competition + higher specificity = better unit economics.
  • Use SEM to validate SEO potential. If a keyword converts well on paid search, it's worth pursuing on organic search. If it doesn't convert on paid, SEO won't save it. WHY: SEM is fast keyword validation. SEO takes months to rank. Using SEM to test before committing to SEO saves months.

Examples

Scenario: SaaS founder with rising CAC

Trigger: "Our Google Ads CAC was $80 six months ago. Now it's $140. Product price $79/month. What's going on?"

Process: (1) Calculate current metrics by ad group. Find 3 groups with CTR < 1.5% — Quality Score penalty spiral. (2) Unit economics check: $79 × 30% margin × 12 months = $284 LTV profit. $140 CAC is still profitable (LTV:CAC 2:1) but trajectory is wrong. (3) Prune: 15 keywords have CPA > $200 — kill them. (4) Restructure: 3 broad ad groups → 12 tight ad groups with specific copy. (5) Long-tail expansion: add 40 specific variants targeting buyer intent phrases.

Output: Clear diagnosis (Quality Score + bad ad group structure), pruning list, restructuring plan.

Scenario: Testing SEM as a new channel

Trigger: "We want to try Google Ads for our B2B analytics tool. $1k test budget. Never run ads before."

Process: (1) Research existing search volume on category terms via Keyword Planner. (2) Check competitor CPCs — if top-of-page bid is $8, $1k gives 125 clicks. (3) Design test: 5 keyword clusters, tight ad groups, 2 ads per group, 1 landing page per cluster. (4) Profitability filter: target CPA < $200 (assuming $50/month × 30% × 12 = $180 LTV profit = need CPA < $180). (5) Test for 2 weeks, measure. If profitable → scale. If not → prune and try long-tail.

Output: Structured first test with clear profitability criteria and scale/abandon decision rule.

Scenario: Inherited a messy 100k-keyword account

Trigger: "Took over SEM for a company that has 100,000 keywords across 200 ad groups. CAC is all over the place. Where do I start?"

Process: (1) Export current data — spend, conversions, CPA per keyword/ad group. (2) Apply profitability filter to every row. Identify the 20% of keywords producing 80% of conversions. (3) Quality Score audit — find ad groups in the penalty spiral. (4) Aggressive prune: pause everything unprofitable (expect to cut 30-60% of keywords). (5) Restructure remaining into tight ad groups. (6) Re-test over 2 weeks and compare.

Output: Prioritized cleanup plan, pruning list, restructuring roadmap — the Archives.com pattern of 100k → 50k.

References

License

This skill is licensed under CC-BY-SA-4.0. Source: BookForge — Traction: A Startup Guide to Getting Customers by Gabriel Weinberg and Justin Mares.

Related BookForge Skills

Install related skills from ClawhHub:

  • clawhub install bookforge-bullseye-channel-selection — Select SEM via Bullseye before deep optimization
  • clawhub install bookforge-seo-channel-strategy — SEO complements SEM for category terms
  • clawhub install bookforge-traction-channel-testing — CAC/LTV framework applies here

Or install the full book set from GitHub: bookforge-skills

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权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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