linkedin-mcp-server: Skill for Claude Code

.agents/skills/btca-local/SKILL.md

btca-local is a skill for Claude Code, Codex from tr4m0ryp/linkedin-mcp-server. It costs 16 tokens per session (594 once invoked), scanned A, a copy of btca-local, Apache-2.0.

A local tool for searching Git repositories that have already been cloned onto the machine. BTCA means Better Context App.

In plain words
What is it for?
Use it to list available local repositories and investigate a specific repository with code examples.
Why use it?
It helps answer questions about local code without relying on memory or searching unrelated repositories.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is tr4m0ryp/linkedin-mcp-server's own configuration. It tells Claude Code and Codex how to work on linkedin-mcp-server itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything linkedin-mcp-server configures →

Reuse

Borrowing it

Nothing to install: this file belongs to tr4m0ryp/linkedin-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/tr4m0ryp/linkedin-mcp-server/main/.agents/skills/btca-local/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/tr4m0ryp/linkedin-mcp-server

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for btca-local

README.md
[![agentmods](https://agentmods.dev/badge/skills/tr4m0ryp/linkedin-mcp-server/btca-local/github.svg)](https://agentmods.dev/skills/tr4m0ryp/linkedin-mcp-server/btca-local)
Your own site
<a href="https://agentmods.dev/skills/tr4m0ryp/linkedin-mcp-server/btca-local"><img src="https://agentmods.dev/badge/skills/tr4m0ryp/linkedin-mcp-server/btca-local/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for btca-local

Your own site · 80×15
<a href="https://agentmods.dev/skills/tr4m0ryp/linkedin-mcp-server/btca-local"><img src="https://agentmods.dev/badge/skills/tr4m0ryp/linkedin-mcp-server/btca-local.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 594 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00016 $0.00594
Opus 5.5 $0.00006 $0.00238
Sonnet 5.5 $0.00003 $0.00119
Haiku 4.5 $0.00002 $0.00059

Measured 1mo ago against content hash bd9322a4bae9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

btca-local scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to btca-local — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/btca-local/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BTCA Local

BTCA Local, aka "The Better Context App Local" is a simple app defined as a skill file. The purpose of this app is to search git repos cloned onto this machine.

the BTCA Search Workflow

<end_goal> a clear, concise answer to the question with code examples </end_goal>

Startup Cases:

This skill can be invoked in a couple different ways, and your behavior should reflect that:

user invoked without extra context/question

this is the "app startup" state, almost as if a terminal app was booted up.

Your job is to search the working directory ~/.btca/agent/sandbox at the top level, just to get a list of all the repos that have been previously cloned

Then you should simply output the following markdown (filling in the existing repos):

# BTCA Local

_use your coding agent to search any git repo locally_

Previously searched:

- repo 1
- ...

Give me a question and the link to a git repo to get started!
(we can also clean out or pre-load some resources to this list...)

Read the full file on GitHub · 79 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 79 lines · 16 tokens per session scan A bd9322a4bae9

Subscribe to this mod's changes

btca-local is a skill published in the GitHub repository tr4m0ryp/linkedin-mcp-server (3 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 594 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to btca-local, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

b2b-marketing-playbook

Complete B2B marketing pipeline combining LinkedIn content, cold email sequences, and webinar funnels. Designed for SaaS founders doing $0–$1M ARR who need predictable lead generation. By @WeiYipei.

Gingiris-1031/gingiris-skills · 53 tokens

bewerbungsexperte

Spezialist fuer den gesamten Bewerbungsprozess. Analysiert Stellenanzeigen, optimiert Profile (LinkedIn/CV) und generiert massgeschneiderte Anschreiben. Generiert ASCII-Lebenslaeufe aus einer SQLite-Datenbank und Ordnerstruktur. cvgenerator.py ist standalone portiert -- keine BACH-Runtime noetig.

ellmos-ai/skills · 78 tokens

LinkedIn Automation

Automate LinkedIn marketing, lead generation, content publishing, and professional networking.

claude-office-skills/skills · 19 tokens

linkednav

Run LinkedIn outreach on the user's own LinkedNav account through the LinkedNav MCP server. Use when the user wants their outreach audited, a campaign created, launched, paused or diagnosed, leads found from buying signals, outreach messages written, replies read or answered, contacts enriched, or results reviewed…

linglistack/linkednav-mcp · 70 tokens

gorilla-lead-finder

Find your first SaaS users by searching Reddit, X, YouTube, LinkedIn, and Bluesky for people already describing the problem your product solves. Ranks every result by buying intent and drafts platform-tuned outreach. Backed by the Gorilla API at https://usegorilla.app.

opusforge/gorilla-mcp · 66 tokens

linkedin-engage-plan

Design a multi-touch warming sequence for one target so they recognise you before you ever message them. Use when you have a specific person worth warming up before any pitch.

styfinity/linkedin-engine · 38 tokens