linkedin-claude-automation: Instructions file for Codex

AGENTS.md

linkedin-claude-automation AGENTS.md is an instructions file for Codex, OpenCode from dzigi00/linkedin-claude-automation. It costs 1,711 tokens per session, scanned A, original, MIT.

Repository instructions for a LinkedIn automation project, covering development commands, scraping behaviour, tool responses, and bug-report verification. LinkedIn is a professional networking website.

In plain words
What is it for?
Installing dependencies, linting, formatting, type-checking, testing, running the server, and implementing LinkedIn scraping with stable navigation rules.
Why use it?
They give an AI coding assistant the project-specific rules needed to develop and run the scraper consistently.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions CLAUDE.md; positional $N argument; mentions Claude Code.

This is dzigi00/linkedin-claude-automation's own configuration. It tells Codex and OpenCode how to work on linkedin-claude-automation 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-claude-automation configures →

Reuse

Borrowing it

Nothing to install: this file belongs to dzigi00/linkedin-claude-automation. 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/dzigi00/linkedin-claude-automation/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/dzigi00/linkedin-claude-automation

Made for: Codex, OpenCode.

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 linkedin-claude-automation AGENTS.md

README.md
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Your own site
<a href="https://agentmods.dev/instructions/dzigi00/linkedin-claude-automation/agents-md"><img src="https://agentmods.dev/badge/instructions/dzigi00/linkedin-claude-automation/agents-md/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 linkedin-claude-automation AGENTS.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/dzigi00/linkedin-claude-automation/agents-md"><img src="https://agentmods.dev/badge/instructions/dzigi00/linkedin-claude-automation/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 1,711 This file is loaded in full into every session.
When invoked 1,711 The same file — it is already loaded in full.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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 $0.01711 $0.01711
Opus 5 $0.00856 $0.00856
Sonnet 5 $0.00342 $0.00342
Haiku 4.5 $0.00171 $0.00171

Measured 9d ago against content hash 95b11324aa00, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

linkedin-claude-automation AGENTS.md scanned grade A with 1 finding 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 9d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -D /tmp/mcp-headers -X POST http://127.0.0.1:8000/mcp \
AGENTS.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Development Commands

  • Use uv for dependency management: uv sync (dev: uv sync --group dev)
  • Lint: uv run ruff check . (auto-fix with --fix)
  • Format: uv run ruff format .
  • Type check: uv run ty check (using ty, not mypy)
  • Tests: uv run pytest (with coverage: uv run pytest --cov)
  • Pre-commit: uv run pre-commit install then uv run pre-commit run --all-files
  • Run server locally: uv run -m linkedin_mcp_server --no-headless
  • Run via uvx (PyPI/package verification only): uvx linkedin-scraper-mcp
  • Docker build: docker build -t linkedin-mcp-server .
  • Install browser: uv run patchright install chromium

Scraping Rules

  • One section = one navigation. Each entry in PERSON_SECTIONS / COMPANY_SECTIONS (scraping/fields.py) maps to exactly one page navigation. Never combine multiple URLs behind a single section.
  • Minimize DOM dependence. Prefer innerText and URL navigation over DOM selectors. When DOM access is unavoidable, use minimal generic selectors (a[href*="/jobs/view/"]) — never class names tied to LinkedIn's layout.
  • Detection must be locale-independent. Classification logic — connection state, action availability, button identity — must rely on URL patterns (/preload/custom-invite/?vanityName=USER, /in/USER/edit/intro/, /messaging/compose/), attribute presence (aria-label exists, aria-expanded exists, aria-disabled exists), or structural counts — never on text values like "Connect", "Follow", "Message", "1st", "Pending". The verb in an aria-label is locale-dependent; whether the attribute exists is not. Where text is genuinely the only signal, guard it behind an explicit per-locale table and document the limitation in code.

Tool Return Format

All scraping tools return: {url, sections: {name: raw_text}}.

Optional additional keys:

  • references: {section_name: [{kind, url, text?, context?, value?}]} — LinkedIn URLs are relative paths; value carries non-URL identifiers (e.g. company URN id for kind: "company_urn")
  • section_errors: {section_name: {error_type, error_message, issue_template_path, runtime, ...}}
  • unknown_sections: [name, ...]
  • job_ids: [id, ...] (search_jobs only)
  • references["feed"] (get_feed only) — every entry is kind: "feed_post"; non-post anchors (sidebar profiles, employer logos) are filtered. URLs may carry either /feed/update/<urn>/ (DOM-anchor-derived) or /posts/<slug> (SDUI-derived) form; both are valid LinkedIn permalinks. Cap is 50 entries, matching get_feed's num_posts ceiling.

Read the full file on GitHub · 119 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. 9d ago First seen · 119 lines · 1,711 tokens per session scan A 95b11324aa00

Subscribe to this mod's changes

linkedin-claude-automation AGENTS.md is an instructions file published in the GitHub repository dzigi00/linkedin-claude-automation (0 stars, last pushed 3mo ago), licensed MIT. It adds 1,711 tokens to every session, about $0.0086 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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