
SignalPipe
io.github.AbYousef739由 GitHub 帳號 AbYousef739 發布v2.1.3更新於 Oct 24, 2026
Buying-intent judgement for AI agents: a three-judge panel scores any text as buyer or not.
概覽
SignalPipe 將文字判定為購買意圖,把合格潛在客戶連同草擬回覆加入佇列,並追蹤潛在客戶的培育進度。
- 可以做什麼
- SignalPipe 判斷貼文、電子郵件或工單的作者是否有購買意圖,對邊界情況使用三名評審組成的小組進行裁決。它列出待處理潛在客戶及其評分和草稿,允許助理核准、拒絕或刪除任務,並可上傳由宿主模型撰寫的草稿。培育引擎跨 14 種訊號類型追蹤潛在客戶的溫度並產生下一則外聯訊息,可選的 Reddit 傳送器使用使用者自己的憑證發布已核准的留言和私訊。
- 適用情境
- 當助理需要監控資訊來源或貼上的文字以發現購買訊號,並管理帶有草擬回覆的銷售潛在客戶佇列時使用。它適合從事社群銷售或潛在客戶資格評估的團隊,希望在工作流程中完成評分、起草和潛在客戶培育。
- 執行需求
- 遠端 MCP 端點 Authorization Bearer 操作員金鑰。託管的評分和起草後端需要付費訂閱。可選的 Reddit 傳送需要 REDDIT_CLIENT_ID、REDDIT_CLIENT_SECRET、REDDIT_USERNAME 和 REDDIT_PASSWORD 環境變數。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 SignalPipe,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/io.github.AbYousef739%2Fsignalpipe/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。
{
"mcpServers": {
"signalpipe": {
"type": "http",
"url": "https://api.signalpipe.io/mcp"
}
}
}README
SignalPipe
Agentic sales pipeline — buying-intent detection, swarm-scored lead qualification, and prospect nurturing for OpenClaw agents.
SignalPipe judges whether the author of a post, email or ticket wants to buy. Your agent brings the text from anywhere it reads, including X through your own X API access, and an optional scout reads the RSS or Atom feeds you choose. Three independent judges rule on every borderline signal, each kept lead gets a drafted reply that answers what the person actually asked, and only real leads reach you for approval. Works with any OpenClaw-compatible agent — or connect directly via MCP from Claude Code, Cursor, or Windsurf.
signalpipe.io · Smithery · Glama
What It Does
Top of funnel — Signal Acquisition (Mantidae): Your agent brings text from anywhere it reads, and the optional scout reads the RSS or Atom feeds you choose every cycle. Clear-cut posts are decided on content alone; borderline ones go to three independent judges (Skeptic, Analyst, Optimist), and when they split you see it. Only real leads reach your queue, each with a drafted reply that answers what the person asked and mentions your product only when they asked for a tool.
Competitor-switch posts are hard-floored and always reach your queue regardless of score.
Mid/bottom of funnel — Nurture Engine: Tracks every prospect's temperature (0–100) across 14 signal types. Automatically selects the right persona (Educator → Consultant → Closer → Re-engager). Remembers objections permanently — if someone said the price is too high, that angle is never repeated. Never spams. One-directional mode transitions.
Execution — Sender (v2.0):
The brain scores, drafts, and approves; the plugin can now also send. An optional background sender holds a live stream open to the brain, receives the missions you've already approved, and posts reddit_comment / reddit_dm on Reddit with your own credentials. The math runs on us, the sending runs on you — your Reddit credentials and LLM keys never reach SignalPipe. twitter_reply is handled by the standalone signalpipe-daemon. The sender is opt-in: set the REDDIT_* env vars to enable it, or ignore it entirely and stay MCP-only. Private messages go only to someone who asked for one: Reddit and X both require the recipient's consent before an app sends one. SignalPipe never auto-sends a DM or an X reply; each waits for your approval.
Tools (29 total)
Signal Acquisition
Nurture Engine
Sender
Reddit-only; requires the optional REDDIT_* env vars. Contains no scoring or drafting — it only posts pre-approved missions with your credentials.
Reader
Reads feeds from this machine. No credentials and no extra dependencies.
MCP Support
SignalPipe exposes all tools as an MCP server — no OpenClaw plugin install needed.
Connect from Claude Code, Cursor, or Windsurf — add this URL to your MCP config:
Auth: Authorization: Bearer YOUR_OPERATOR_KEY
Once connected, ask your agent:
- "Show me my leads"
- "Reject the first one — it's a founder promoting their own tool"
- "Who should I follow up with today?"
Live Session Example
A typical morning lead review inside your OpenClaw agent or Claude.ai via MCP.
You: Show me today's leads.
Agent: 2 leads ready. Lead 1 is a competitor-switch signal, score 91 — Closer draft, proposes a direct next step. Lead 2 is a genuine need with flexible budget, score 68 — Advisor draft, leads with their real problem. Lead 3 was auto-rejected by the swarm. Approve 1 and 2, or edit first?
You: Lead 1 is good, approve it. For lead 2 change the draft to: "Hey Rachel — we solve exactly this. Most ops teams are running automations within a day. Want me to show you how a team like yours uses it?"
You: Rachel just replied — she's interested. Log it.
Agent: Rachel is in Sales mode, temperature 45. Consultant persona active — qualify and show fit, no hard sell yet.
You: Who's hottest? Generate a message for them.
Agent: Closing mode, friction-removal tactic. Her previous pricing objection is permanently on record — the AI avoided that angle automatically.
Quick Start
1. Get a backend + operator key
Subscribe at signalpipe.io, sign in to the console with the email you paid with, and create your SIGNALPIPE_OPERATOR_KEY there (it is shown once). The backend URL is https://api.signalpipe.io. No infrastructure to manage.
2. Install
Via OpenClaw:
Via MCP (no plugin install): Add the MCP server URL to Claude.ai, Cursor, or Windsurf — see MCP Support above.
3. Set environment variables
Optional — to run the in-plugin Reddit sender (v2.0): add a Reddit "script" app's credentials (create one at https://www.reddit.com/prefs/apps on the sending account; since November 2025 Reddit reviews new API apps under its Responsible Builder Policy before issuing them). These stay on your machine and are never sent to SignalPipe.
4. Configure a product
Ask your agent:
"Set up my product. It's called AcmeTool, it automates repetitive ops workflows, and it's bought by ops leads and founders."
The agent drafts buyer-voice anchors with signalpipe_suggest_anchors (for example "we're drowning in the same manual handoffs every week"), shows them to you to edit, then adds the product. Before adding a feed, have it run signalpipe_preview_station on the feed: it says whether buyers actually post there.
The signal engine activates on the next scout cycle.
How Scoring Works
Every incoming post passes through two sequential pipelines.
Pipeline 1 — Scoring (backend):
- Optional keyword gate — only if you set
buy_signal_keywords. A post matching none of them is dropped before anything reads it, so leave the list empty unless your buyers use a fixed vocabulary. - Multi-factor semantic scoring — embedding similarity, urgency, specificity, and keyword density. Multilingual: English, Spanish, French, German, Portuguese, Finnish.
- Sarcasm detection — distinguishes genuine buyers from venting or irony. Fails open — real leads are never suppressed by the sarcasm check.
Pipeline 2 — Swarm Drafting (managed backend):
Posts that survive scoring reach a 3-judge AI swarm:
The judges run concurrently, and their scores are fused via a weighted ensemble. Low-confidence leads are auto-rejected — they never reach your queue. When the judges keep a lead, a separate writer drafts the reply: one concrete answer to what the person asked, in two or three sentences, mentioning your product only when they asked for a tool. If the writer is unavailable, the judges' own draft is used instead, pitched to how strong the signal is:
- Closer (highest-intent): Proposes a concrete next step — demo link, trial, or direct ask
- Advisor (mid-intent): Consultative — acknowledges situation, introduces product naturally
- Educator (early-stage): Value-first — answers their question, mentions product only if it fits
Reinforcement learning: Every approve/reject adjusts the source station's RL weight — each listening feed (subreddit, HN search, RSS source) carries its own multiplier. Approvals reward the feed; rejections are reason-aware, with the penalty sized to how bad the signal was — spam is penalised hardest, then wrong-audience, then weak or no-reason rejections, while sarcasm and wrong-product are lighter and "already a customer" carries no penalty. Per-station scoping means one noisy feed gets demoted without penalising the rest of the product's sources.
Temperature Model
Mode is intent-based, not pure temperature. Brand-new prospects start in
nurture regardless of their starting temperature and only move out once a
real signal lands.
14 signal types map to calibrated heat deltas: booked_demo, asked_pricing, viewed_content, replied, clicked_link, not_decision_maker, ghosted_3_days, no_time, competitor, too_expensive, not_interested, bad_timing, ghosted_7_days, opted_out. With the reply text in hand, signalpipe_record_reply reads it and sets the signal for you.
One-directional mode transitions — no oscillation, no spam. Objection memory — permanently recorded and injected into every future message so the AI never repeats a failed angle.
Pricing
The plugin and the daemon are free and MIT licensed. The managed brain — scoring and drafting — is a subscription, metered in judgements (one three-judge panel run). Text that is clearly noise or clearly a buyer is decided without convening the panel and spends nothing.
Billed monthly through Stripe; cancel any time from your billing page. Every scoring call returns how much of the month is left. Current details: signalpipe.io/pricing.
Reading your feeds on this machine
Some stations can be read from your own machine instead of by the brain: they show read_by: "client" in /stations/list. signalpipe_read_feeds fetches those feeds from here, at most 50 posts per feed and a minute between feeds (Reddit limits how fast one machine may read), and hands each page to the brain, which scores the posts as if its own scout had read them. Run it once, or with every_minutes to keep reading. The standalone signalpipe-daemon does the same with signalpipe-daemon read.
Checking a feed before you add it
signalpipe_preview_station reads a candidate feed on this machine and has the brain judge its best-matching posts, without saving anything. The verdict comes from thresholds fixed in advance: VIABLE (real buyers post here), MARGINAL (a trickle), ON-TOPIC, NOT IN-MARKET (people discuss your topic but nobody is asking to buy, usually makers or support questions), NO BUYERS, or NO DATA (nothing could be judged; the explanation says why, such as an empty or stale feed or keywords that blocked every post). Each judged post costs one judgement. Which communities you listen to decides results more than any setting, so check before you add.
Sending from your own accounts
The drafts are written by AI. Reddit asks that AI-generated content be disclosed, and both Reddit and X act against automated posting, so read and edit each draft in your own words before it goes out. Public Reddit comments, X replies and DMs are never sent without a person approving each one.
The in-plugin sender posts approved missions with a Reddit script app on your account. Since 11 November 2025 Reddit issues new API apps only after a manual approval, so if you do not already have one, skip the sender: approve drafts in your agent, post them yourself, and the queue works the same. X sending lives in signalpipe-daemon and needs a paid (pay-per-use) X API account.
License
Plugin: MIT. The managed brain is a hosted service and is not distributed.
來源:README.md,提交 39128ea
工具
0版本歷史
5- v2.1.3最新Sep 29, 2026
- v2.1.2Sep 29, 2026
- v2.0.5Sep 25, 2026
- v2.0.4Sep 24, 2026
- v1.5.0Sep 16, 2026
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