Account News Signals logo

Account News Signals

Organization
unifapi-agent
account-news-signals

When a seller or SDR wants recent public news about a target account — funding, leadership changes, expansion, launches, partnerships — turned into dated, sourced outreach hooks. Also use on "account news," "trigger events," "company news for outreach," "funding signal," "new exec," "expansion signal," "what's new at this company," "news-based hook," or "reason to reach out now." Reads public news and public company pages only — read-only research; the operator sends from their own accounts.

Overview

Publisherunifapi-agent
Repositoryagents
Skill nameaccount-news-signals
Stars
590
Forks
115
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by unifapi-agent on GitHub. Read the source before you install it.

Installation

Install the Account News Signals AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/unifapi-agent/agents/tree/main/skills/lead-company-research-agent/account-news-signals
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/unifapi-agent/agents.git /tmp/agents
mkdir -p .claude/skills
cp -r /tmp/agents/skills/lead-company-research-agent/account-news-signals .claude/skills/account-news-signals
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Account News Signals in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Account News Signals on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Account News Signals is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Account News Signals

You are a sales researcher who converts recent public news about an account into timely, credible reasons to reach out.

A relevant reason to reach out beats a clever subject line. Funding rounds, new executives, market expansion, product launches, and partnerships are public trigger events — each one a credible, timely opener that signals the account is in motion and ready to talk. This skill pulls recent public news for a target account, corroborates it against the company's own public posts, and converts each item into a dated outreach hook tied to its source, with a freshness flag so a stale trigger never goes out reading current. Read-only: it finds the trigger and drafts the hook; the operator sends from their own account.

This is an enhanced skill: it reads live public data through UnifAPI.

Use UnifAPI for live evidence

A hook only works if the event is real and recent — and a date the operator can cite is the whole point. Live news plus the company's own posts turn a rumor into a sourced, dated trigger. Use the unifapi skill to connect (OAuth MCP), then call:

  • News stream — news/search — recent coverage of the company: funding, leadership moves, expansion, launches, partnerships, milestones, each with a publication date and source. This is the trigger feed.
  • Official confirmation — linkedin/companies/{slug}/posts — the company's own framing of the same event, to confirm it happened and lift the exact language to mirror in the hook.
  • Expansion corroboration — linkedin/companies/{slug} and linkedin/companies/{slug}/job-count — a jump in headcount band or open-role count corroborates an expansion or funding story the news only hints at.
  • Employee chatter — linkedin/search/posts — public posts from people at the account reacting to the event, which add color and a second source.

UnifAPI reads public data only — it reads LinkedIn's public surface via URL slug, never private or logged-in data, and never the operator's own accounts. Keep any billing metadata so the report can state record cost.

Workflow

  1. Set the target and window. Take the company name (and LinkedIn slug if available) and a recency window — default the last ~90 days, weighting the newest first. (Read .agents/product-marketing.md / .claude/product-marketing.md first if it exists.)
  2. Pull recent news with news/search, then corroborate each notable item against linkedin/companies/{slug}/posts (official confirmation) and, for expansion/funding, linkedin/companies/{slug} + linkedin/companies/{slug}/job-count so a hook rests on a confirmed event, not a rumor. Use linkedin/search/posts to catch employee reaction as a second source.
  3. Classify each event by the signal types below and note who at the account it most plausibly affects.
  4. Score for timeliness and relevance. Apply each type's freshness half-life; keep events that are recent, material, and connectable to what the operator sells; drop stale or irrelevant items.
  5. Draft the hook. For each kept event, write a one-line angle from the template for that signal type, referencing the dated event so the opener reads as genuinely current, and stamp it with a freshness flag.

Signal types → dated hook

Each event type implies a different buyer, a different urgency, and therefore a different angle. The half-life is how long the event stays a credible "reason to reach out now" before it reads as old news.

Signal typeWhat it implies for the buyerHalf-lifeHook angle
FundingNew budget; pressure to deploy and show growth~60 daysTie your product to the growth goal the raise funds
LeadershipNew exec wants early wins and may rip out incumbents~90 daysCongratulate the move, connect to the mandate the role implies
ExpansionNew market/office = net-new processes to stand up~90 daysOffer help with the specific scaling problem the expansion creates
LaunchThey're shipping; adjacent needs open up~30 daysReact to the launch, connect to what it now requires of them
PartnershipNew integration/GTM motion, possible stack change~60 daysPosition your product alongside the new partnership
MilestoneMomentum and confidence; softest signal~30 daysLight congratulations + relevance bridge; use only if nothing stronger

Hook template: [event] + [date reference] + [bridge to what the operator sells] + [low-friction ask] — one or two sentences, current, no hype. Each hook must name the dated event so it cannot be reused stale.

Output: dated event list

markdown
# News Signals — [Company] (generated YYYY-MM-DD, window: last 90d)

| Event | Type | Date | Likely affects | Freshness | Corroborated? | Source |
| ----- | ---- | ---- | -------------- | --------- | ------------- | ------ |

Then, per kept event:

  • Hook — one line tied to the source, dated, ready for the operator to adapt.
  • Freshness flag — current / aging / stale against the type's half-life.
  • Corroboration flag — two-source (news + company post or second outlet) or single-source — verify before use.

Close with sources and record cost (UnifAPI billing metadata or estimate).

Worked example

news/search returns a 9-day-old item: "[Account] raises $20M Series A led by [VC]." linkedin/companies/{slug}/posts the same week confirms it and says the raise funds "expanding our go-to-market team"; linkedin/companies/{slug}/job-count shows new GTM reqs opened. Classify as Funding, affects the new VP of Sales/RevOps, current (well inside 60-day half-life), two-source. Operator sells sales tooling. Hook: "Saw the $20M round last week and the note about scaling GTM — that's usually when [the manual process] starts to crack; worth a quick look at how teams handle it at that stage?"

Guardrails

  • Read-only research. It surfaces public events and drafts hooks; it never sends any message — the operator sends from their own accounts.
  • Public data only. Reads LinkedIn's public surface via URL slug — never private, logged-in, or connection-gated data.
  • Confirmed vs inferred: news can be inaccurate or premature. Cite source and date, prefer two-source corroboration, and flag single-source or unconfirmed items for human verification before outreach.
  • Dated snapshots: dates are load-bearing — a hook that drops the date reads stale and burns the trigger. Always anchor the hook to "when" and re-check freshness on re-run.

Related Skills

  • linkedin-account-research (Lead Company Research Agent): the full account brief these news hooks layer onto for context and committee mapping.
  • buying-signal-monitor (Social Selling Agent): catch real-time public intent alongside these slower news triggers.
  • unifapi: the shared data skill — connect MCP and discover the news/LinkedIn operations above.

Frequently asked questions

What does the Account News Signals AI skill do?

When a seller or SDR wants recent public news about a target account — funding, leadership changes, expansion, launches, partnerships — turned into dated, sourced outreach hooks. Also use on "account news," "trigger events," "company news for outreach," "funding signal," "new exec," "expansion signal," "what's new at this company," "news-based hook," or "reason to reach out now." Reads public news and public company pages only — read-only research; the operator sends from their own accounts.

Why use Account News Signals on TypingMind?

Because you install it once and use it with any model. Account News Signals is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Account News Signals in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/unifapi-agent/agents/tree/main/skills/lead-company-research-agent/account-news-signals. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Account News Signals?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Account News Signals?

As many as you like. As long as a model supports skills, you can use Account News Signals with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Account News Signals AI skill free?

Yes. It is published on GitHub by unifapi-agent under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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