Linkedin Signal Stack
Pull five-plus real, checkable signals on one target and stack them into a 3-line signal brief a message can be built on. Use before writing any outreach so the message reads like 30 minutes of homework.
Install
$ agentstack add skill-styfinity-linkedin-engine-linkedin-signal-stack ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-styfinity-linkedin-engine-linkedin-signal-stack) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
LinkedIn Signal Stack
The lift in outreach is not the message, it is the signal stack underneath it. This skill does the homework: five-plus real signals per target, distilled to the one sharpest thing to open on.
Inputs
- A target (profile and/or company) to research: $ARGUMENTS
- The brief (ICP, voice, offer, pains) loads automatically, so the signals are filtered for what matters to this operator.
Do this
- Gather signals that matter on this one target. Aim for five or more from across:
- Recent funding, raise, or revenue milestone.
- An exec move or a new hire (especially in growth, sales, or rev ops).
- A phrase or priority lifted straight from a current job description they have open.
- Their last post (the hook, the claim, the question they raised).
- Any company news from the last 14 days (launch, press, partnership, hiring spike).
- Verify each one. If a signal cannot be checked against a real, dated source, leave it out. No guessing, no inference dressed as fact.
- Stack them into a 3-line signal brief: what is going on, why it is happening now, and the angle it opens.
- Pick the single sharpest signal: the one a peer would notice and the target would feel seen by.
Output
A signal brief per target, labelled clearly: the five-plus verified signals (each with its source), then the 3-line brief, then "Open on:" with the single sharpest signal. Hand this to a message-writing skill like /linkedin-first-dm or /linkedin-connection-note.
Rules
- Only real, checkable signals. Every one carries its source. If it cannot be verified, it does not go in.
- Drafts research only. Pulling signals live (profiles, posts, company pages) needs the connected CLI/MCP layer wired to the operator's own session or a provider key; nothing is scraped by default.
- The operator approves what gets used. This skill never sends.
- No em-dashes. No filler. Operator-grade signals only.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: styfinity
- Source: styfinity/linkedin-engine
- License: MIT
- Homepage: https://styfinity.com
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.