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cargo-gtm货物总吨位

Agent Skill

cargo-gtm 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

423

周安装

18

GitHub Stars

12

下载量

148
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:cargo-gtm(货物总吨位)
来源仓库:https://github.com/getcargohq/cargo-skills
仓库路径:skills/cargo-gtm
安装命令:
npx skills add https://github.com/getcargohq/cargo-skills --skill cargo-gtm
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/getcargohq/cargo-skills --skill cargo-gtm

简介

GTM 决策路由与安全网关,管控获客、账户研究、联系人丰富化与信号监控等执行前置条件。

  • 设定质量默认值与提供商安全门控,确保营销活动合规性与效果可控。
  • 适用于大规模客户拓展、个性化营销与 Campaign 激活等 GTM 核心场景。
  • 使用前必须阅读 workflows/global-standards.md 确保输出符合既定规范要求。
  • cargo-gtm 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Cargo GTM — Meta Skill

Use this skill for prospecting, account research, contact enrichment, verification, lead scoring, personalization, signal monitoring, and campaign activation.

1) What this skill governs

  • Route GTM decisions, safety gates, and provider/quality defaults before execution.
  • Keep long command chains and tooling nuance in sub-docs; provider-specific implementation detail in provider-playbooks/*.md.
  • Anchor recipes in credits-based actions (the high-value action calls). Free CRUD (createLead, getLead, deleteRecords) doesn't need this skill — agents can compose those ad hoc.

Process / goal

The user is generally trying to go from "I have an ICP" to "Here's a list of prospects with verified emails and personalized signals." They may be anywhere in this process — guide them along.

Discovery order: companies first, then people. When the task requires finding contacts at companies matching criteria (portfolio, ICP, hiring signal), discover the company set first, then find people at each company. Don't start with broad people-search queries.

Documentation hierarchy

2) Read behavior — MANDATORY before any execution

STOP. Do not call any provider, run any cargo-ai orchestration action execute command, or write any search query until you have opened the correct sub-doc for your task.

These docs encode what works, what fails, and why. They contain validated parameter schemas, cheapest-provider mappings, parallel execution patterns, sample payloads, and known pitfalls. Reading the right doc for 10 seconds saves 10 failed action calls, wasted credits, and garbage output.

Routing rules — match your task to a doc and READ IT

When the task involves…You MUST read this doc firstWhat it gives you
Finding companies, finding people, building lead lists, prospecting, portfolio/VC sourcing, contact finding at known companiesguides/finding-companies-and-contacts.mdProvider filter schemas, cheapest-source decision tree, parallel patterns, role-based search rules, portfolio/VC shortcuts, contact-finding patterns.
Enriching companies or contacts, finding emails/phones/LinkedIn, waterfall enrichment, signal lookup (job change, funding, tech stack), coalescing dataguides/enriching-and-researching.mdWaterfall patterns with fallback chains, when to use cargo-native vs waterfall vs FullEnrich vs peopleDataLabs, email/phone/LinkedIn fallback orders, signal segments, output retrieval via run download-outputs.
Writing cold emails, personalizing outreach, lead scoring, qualification, sequence design, campaign copyguides/writing-outreach.mdLLM provider routing (openAi/anthropic/perplexity/gemini), prompt templates, scoring rubrics, email length/tone rules, personalization patterns.
Building or modifying a recurring workflow (cron / webhook / scheduled tool / play), designing step sequences, triggers, deploy/verify cycles../cargo-orchestration/SKILL.md (capability) + apply-patterns from this skill's recipesSchema for tool/play workflows, node graph syntax, polling strategies, output retrieval.

Recipes: step-by-step playbooks (check before executing)

Scan this list and read the recipe matching your task. When a recipe matches: follow it step-by-step as your execution plan.

RecipeUse when…
recipes/prospecting.mdEnd-to-end find → enrich → verify → sync (P1/P2/P3 variants)
recipes/build-tam.mdBuilding a Total Addressable Market list at scale (100–10,000 companies)
recipes/linkedin-url-lookup.mdResolving a person's LinkedIn profile URL from name + company with strict identity validation
recipes/portfolio-prospecting.mdInvestor / accelerator → portfolio companies → contacts
recipes/job-change-monitoring.mdwaterfall.detectJobChange (cargo-unique) on a contact segment
recipes/funding-watch.mdTracking companies that recently raised funding
recipes/tech-intent.mdFinding companies by tech-stack or hiring-intent signals
recipes/icp-discovery.mdDiffing Closed-Won vs Closed-Lost segments to surface ICP signals

If none match, scan the phase docs above for the closest pattern and adapt — or invoke agents/execution-plan-creator.md to compose a custom chain with provider/action slugs and cost estimates.

3) Priority provider stack (recipes lead with these 6)

These six credits-based providers cover the full prospecting → enrichment → verification → signal pipeline at the lowest credit cost in the catalog. Every recipe in this skill's recipes/ leads with this stack:

ProviderRoleKey actions (cost in credits)
salesNavigatorSourcingsearchLeads (0.02), searchAccounts (0.05), findCompanyInsights/Metrics/EmployeesCount/Distribution (0.25 each)
cargo (native)Firmographic + signal intelligenceenrichBusinessFirmographics (0.5), …Technographics (1), …FundingAndAcquisitions (0.5), enrichProspectDetails/LinkedinProfile/LinkedinPosts (2), matchBusiness/matchProspect (0.5), 13 more
waterfallMulti-source enrichment + signalenrichContact (2), enrichCompany (1), verifyEmail (0.1), detectJobChange (3), searchProspects (3), findPhone (7)
FullEnrichPremium contact lookupfindEmail (1), findPhone (6), findPhoneAndEmail (7), reverseEmailLookup (2)
theirStackTech-stack + hiring intentsearchTechnologies (0.5), searchJobs (0.5), searchCompanies (0.5)
peopleDataLabsHeavyweight backfillenrichPerson (3), enrichCompany (3), searchPeople (3), searchCompanies (3), queryPeople/Companies (3)

See provider-playbooks/ for per-provider deep dives. See references/stage-action-map.md for the complete cheapest-action-per-stage table across the full 120-integration catalog.

4) Recipe spine (default chain)

1. SOURCE   → salesNavigator.searchLeads / searchAccounts            (0.02–0.05/record)
2. DEDUPE   → cargo.matchProspect / cargo.matchBusiness              (0.5/record)
3. ENRICH   → cargo.enrichBusinessFirmographics / Technographics
              + waterfall.enrichContact / enrichCompany              (0.5–2/record)
4. SIGNAL   → cargo.enrichBusinessFundingAndAcquisitions
              + theirStack.searchJobs
              + waterfall.detectJobChange                            (0.5–3/record)
5. CONTACT  → FullEnrich.findEmail (fallback peopleDataLabs)         (1–3/record)
6. VERIFY   → waterfall.verifyEmail                                  (0.1/record)
7. BACKFILL → peopleDataLabs.enrichPerson (only if step 5 missed)    (3/record)

Adapt by phase: drop steps that aren't relevant to the user's goal. For pure sourcing, run step 1 only. For "enrich a list I already have," run steps 2–7.

5) Output retrieval — use run download-outputs, not run download

When the agent needs the actual data produced by an action (enriched fields, found emails, search results), use:

cargo-ai orchestration run download-outputs \
  --workflow-uuid <uuid> \
  --output-node-slug <slug> \
  --format json \
  --is-finished

Returns {"url": "..."} — a signed URL to a CSV/JSON containing only the output node's data. Faster and cheaper than run download (which pulls full run records). See references/output-retrieval.md and ../cargo-analytics/SKILL.md.

6) Action shape rules (every recipe)

Every action JSON in this skill follows the rules in ../cargo-orchestration/references/actions.md:

  • kind: "connector" action shape: {"kind":"connector","integrationSlug":"<slug>","actionSlug":"<slug>","config":{}}. connectorUuid is NOT in config — the platform resolves the workspace's authenticated connector from integrationSlug automatically.
  • For multi-step node graphs: connectorUuid lives at the top level of the node, not in config. Cross-node interpolation uses {{nodes.<slug>.<field>}}. Agent node outputs wrap under .answer (read as {{nodes.<slug>.answer.<field>}}).

7) When stuck — file a workspace report

If a recipe fails repeatedly and the cause isn't obvious, escalate via cargo-ai workspaceManagement report create. See ../cargo-workspace-management/SKILL.md (Reports section).

8) Provider playbooks

Per-provider deep dives for the priority stack. Long-tail providers don't have dedicated playbooks yet — fall back to references/alternatives.md and references/stage-action-map.md.

Priority stack:

9) References

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

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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

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

37.1%
按下载量换算55

Claude

32.39%
按下载量换算48

Cursor

18.11%
按下载量换算27

Gemini CLI

9.59%
按下载量换算14

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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