influencer-discovery

作者 tigerless-labs已验证

Influencer discovery & contact enrichment pipeline that runs as a Claude Code skill — 15 channels, stdlib only, appends to a Google Sheet

79
Stars
13
Forks
Python
语言
2026/8/24
添加时间

⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/tigerless-labs/influencer-discovery

快速入门

使用 influencer-discovery 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

Influencer Discovery

Find creators who bring their own audience — and get their contact info

python zero dependencies platform channels

influencer-discovery is a creator-discovery pipeline that runs as a Claude Code skill. It searches 15 channels for people who bring their own audience — followers, readers, subscribers — pulls their public contact info, and appends them to a Google Sheet. People building their own product are filtered out: they want reach, they don't provide it.

The operating manual is skills/influencer-discovery/SKILL.md. Per-platform capability boundaries (what each API exposes, which credentials it needs, what it costs) live in reference/datalayer/; how contact info is obtained per channel lives in reference/methodology/, where the directory-name prefix is the cooperation priority.

Channels

TierChannels
1 · SocialX/Twitter, Instagram, TikTok, Threads, YouTube, Reddit, Mastodon
2 · Blog platformsDEV.to, Hashnode, WordPress.com, Micro.blog
3 · Personal sitesSelf-hosted blogs, newsletters, podcasts
5 · MediafreeCodeCamp News, HackerNoon

Fetching is polite and read-only: explicit User-Agent, throttled, no anti-bot circumvention. Some channels work with zero credentials; others need an API key or a logged-in session — the per-channel requirements are in datalayer.

Install

No third-party packages, no build step — the pipeline is pure standard library (Python ≥ 3.11). The skill is fully self-contained under skills/influencer-discovery/; clone and run, or copy that one directory into your agent's skills folder:

git clone https://github.com/tigerless-labs/influencer-discovery && cd influencer-discovery
python3 skills/influencer-discovery/scripts/run.py --help

Credentials go in ~/.config/influencer-discovery/.env, never in the repo. Pipeline state lives in ~/.local/share/influencer-discovery/; both paths are overridable via INFLUENCER_DISCOVERY_CONFIG_DIR / INFLUENCER_DISCOVERY_STATE_DIR. Knobs that travel with the code (channel list, throttle parameters, header mapping) stay in skills/influencer-discovery/config/.

Run

python3 skills/influencer-discovery/scripts/run.py --tiers 1 --per-channel 10

--channels / --tiers select channels, --subject sets the topic gate, --min-followers / --min-karma set audience floors. Each run prints a report: planned vs actual, verdict distribution, and the contactable list.

Sheets access

Set INFLUENCER_DISCOVERY_SPREADSHEET_ID and authenticate with a short-lived token minted by impersonating a service account — no long-lived key file on disk. Google blocks adding the spreadsheets scope to plain gcloud ADC ("This app is blocked"), so mint via the iamcredentials API:

T=$(gcloud auth application-default print-access-token)
curl -s -X POST \
  -H "Authorization: Bearer $T" -H "Content-Type: application/json" \
  -d '{"scope":["https://www.googleapis.com/auth/spreadsheets"],"lifetime":"3600s"}' \
  "https://iamcredentials.googleapis.com/v1/projects/-/serviceAccounts/YOUR_SA_EMAIL:generateAccessToken"

Prerequisites: the project has the sheets, iam, and iamcredentials APIs enabled; your ADC identity holds roles/iam.serviceAccountTokenCreator on the service account; the service account can edit the target Sheet. A fresh IAM binding takes ~30s to propagate — a first 403 is normal, retry.

Design invariants

Dedup key is (person, platform)Checked against a local log; URLs are never parsed for identity — same-site different-person collisions taught us that.
Sheet writes are append-onlyThe pipeline creates rows, never edits an existing cell, and aborts if the header row doesn't match its mapping.
Blast radius is one recordA malformed page or link costs that one person, never the channel or the run; intermediate results are flushed as they are produced.
Hostile-input posturePage content is data, not commands — instruction-shaped text in bios and pages is never executed. Every external request leaves through a single read-only choke point.
Contact data never enters the repoReal names, emails, and handles live only in the Sheet; data/ is gitignored end to end.

常见问题

What is influencer-discovery?

influencer-discovery is an open-source data processing skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by tigerless-labs. Influencer discovery & contact enrichment pipeline that runs as a Claude Code skill — 15 channels, stdlib only, appends to a Google Sheet. It has 79 GitHub stars.

Is influencer-discovery safe to use?

Yes. influencer-discovery passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install influencer-discovery?

Clone the repository with "git clone https://github.com/tigerless-labs/influencer-discovery" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is influencer-discovery written in?

influencer-discovery is primarily written in Python. It is open-source under tigerless-labs on GitHub, so you can review or fork the full source.

Are there alternatives to influencer-discovery?

Yes. SkillsLLM lists many other Data Processing skills you can browse and compare side by side. Open the Data Processing category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh influencer-discovery against similar tools.

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