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/li-inbox

@add2c23
by Jake Schincarioljakeschincariol/linkedin-agent-skill1.5k stars
227

Triage the LinkedIn inbox - sort connection requests and DMs into leads, recruiters, peers and spam, and draft the replies worth sending. Use when the user says "my inbox is a mess", "triage my DMs", "should I reply to this", pastes a batch of LinkedIn messages, or is drowning in connection requests.

Use this Skill: https://skilld.dev/gh/jakeschincariol/linkedin-agent-skill/li-inbox

Nothing lands on disk. Nothing to clean up.

Fork this Skill

Edit a local copy. It keeps the author and licence.

SKILL.md

≈78 tokens for metadata: the name and description. ≈636 when used: this file.

Description uses 3.9% of example budget

Before choosing a Skill, your Agent reads its name and description. All available Skills share that space.

  • A shorter description leaves more room for other Skills. This entry exceeds our 1% size suggestion.

In our Claude Code example, all Skill names and descriptions share 8,000 characters. This Skill uses ≈312 characters, or 3.9%.

The 1% threshold is a size suggestion. Longer descriptions can still fit.

Your model, settings, and other Skills decide how much text your Agent can read.

Example settings and source

The example uses a 200k-token context and default Claude Code settings. The count includes the name, description, separators, and when_to_use when present. Codex also counts local file paths.

Skit's source and limits: Codex 0.160.1, Claude Code 2.1.292.

li-inbox

Most LinkedIn inboxes are 80% noise, and the cost of that noise is that the 20% goes unanswered for a week. This skill separates them, then writes only what is worth writing.

Input

The user pastes the messages. Screenshots are fine. Do not log into their account or read their inbox with a browser tool.

Sort into five

bucket signal action
LEAD describes a problem the user solves, or asks about working together reply today, full answer
RECRUITER a role, a company, a salary band reply if the role is real, one line if not
PEER someone in the same field with something to say reply this week, keep it human
ASK wants advice, time, an intro, a favour reply if it is cheap and specific, decline cleanly if not
SPAM agency pitch, lead-gen sequence, crypto, "quick question" with no question archive, no reply

Print the counts first. Seeing "3 leads, 2 recruiters, 41 spam" is most of the value.

Detecting a sequence

Automated outreach has a shape: an invite note with no specifics, a message that arrives within minutes of the accept, "quick question", "I noticed you're in {industry}", a calendar link in message one, then a bump exactly four days later. When you see it, mark it SPAM and say which tell gave it away. The user does not owe a reply to a script.

Replies

  • LEAD - answer the actual question in the message, in full, for free. If it is a fit, the offer is one sentence at the end. If it is not, say so and point them somewhere useful. Both outcomes are good.
  • RECRUITER - if the role is genuinely interesting, ask the three things the message left out: comp band, level, and whether it is in-office. If it is not, one line: not looking, happy to refer, and mean the refer.
  • ASK - if it costs under ten minutes and is specific, do it. If it is "can I pick your brain", decline in one warm sentence and give them the one answer you would have given on the call. That is the polite version and it is also the more useful one.
  • DECLINES are short, warm and final. No "let's revisit in Q3" if there is no Q3.

Output

Grouped by bucket, counts first, drafts only for the buckets that get replies, each one humanized. Then the gate: the user sends them.

INBOX  ·  52 items  ·  3 LEAD, 2 RECRUITER, 4 PEER, 2 ASK, 41 SPAM

SPAM  (41) - archive. 38 are the same sequence: no-specifics invite,
"quick question" within 4 minutes of accept, calendar link in message one.

Source: SKILL.md on GitHub

Skill behaviors

No rule matched.

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

Third-party checks

No alerts29d3 checks · Risk SAFE
  • Gen Agent Trust Hub29d

    The skill is safe but has a surface for indirect prompt injection because it processes untrusted LinkedIn message content without explicit input boundaries.

  • Socket29d

    No alerts

  • Snyk29d

    Risk: LOW · No issues

Provenance

Signed by skilld at add2c23. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 45 minutes ago.

Activeupdated last month

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