research-crawl-linkedin-posts

research-crawl-linkedin-posts is a skill for Claude Code from thangnguyenworkspace/industry-pulse. It costs 35 tokens per session (6,783 once invoked), scanned A, original, MIT.

A tool for collecting LinkedIn posts from multiple supplied URLs through Apify, a web-automation service. It saves each source as Markdown and also creates combined and per-source summaries.

In plain words
What is it for?
Use it to crawl batches of LinkedIn post URLs, limit how many posts are collected, filter by posting date, and optionally include reposts, quoted posts, reactions, or comments.
Why use it?
It avoids gathering posts one profile or page at a time and keeps the raw results organized for later research.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions subagents; positional $N argument.

Good fit Use it to crawl batches of LinkedIn post URLs, limit how many posts are collected, filter by posting date, and optionally include reposts, quoted posts, reactions, or comments.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/thangnguyenworkspace/industry-pulse/research-crawl-linkedin-posts
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add thangnguyenworkspace/industry-pulse --skill research-crawl-linkedin-posts
Clone the repo
git clone --depth 1 https://github.com/thangnguyenworkspace/industry-pulse

Made for: Claude Code.

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 research-crawl-linkedin-posts

README.md
[![agentmods](https://agentmods.dev/badge/skills/thangnguyenworkspace/industry-pulse/research-crawl-linkedin-posts/github.svg)](https://agentmods.dev/skills/thangnguyenworkspace/industry-pulse/research-crawl-linkedin-posts)
Your own site
<a href="https://agentmods.dev/skills/thangnguyenworkspace/industry-pulse/research-crawl-linkedin-posts"><img src="https://agentmods.dev/badge/skills/thangnguyenworkspace/industry-pulse/research-crawl-linkedin-posts/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 research-crawl-linkedin-posts

Your own site · 80×15
<a href="https://agentmods.dev/skills/thangnguyenworkspace/industry-pulse/research-crawl-linkedin-posts"><img src="https://agentmods.dev/badge/skills/thangnguyenworkspace/industry-pulse/research-crawl-linkedin-posts.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,783 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 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 $0.00035 $0.06783
Opus 5 $0.00017 $0.03392
Sonnet 5 $0.00007 $0.01357
Haiku 4.5 $0.00003 $0.00678

Measured 11d ago against content hash 54840414ef15, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

research-crawl-linkedin-posts 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 11d 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.

.claude/skills/research-crawl-linkedin-posts/SKILL.md · 419 lines

How it starts

The opening of the file, as written. The whole thing — 419 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research Crawl LinkedIn Posts

Argument: $ARGUMENTS (required, see Runtime Inputs)

If $ARGUMENTS is empty or missing required fields, STOP and report which fields are absent.


Preamble

Runtime Inputs

Parse from $ARGUMENTS:

--source-urls=[URL1,URL2,...]   [JSON-style array of canonical LinkedIn URLs, non-empty; each entry one of 6 supported shapes per §1.0 Step 2. Singular invocation expressed as a single-element array.]
--raw-output-dir={PATH}          [absolute path to a directory where per-source rendered markdown files will be written]
--max-posts={N}                  [positive integer per-URL cost-cap; MUST be ≥ 1, see §1.0 Step 3 + §6.0 row max-posts-zero]

# Optional power params (omit when not needed):
--posted-limit={ENUM}            [any | 1h | 24h | week | month | 3months | 6months | year]
--posted-limit-date={ISO}        [ISO 8601 timestamp lower-bound cutoff, e.g., 2026-04-21T00:00:00Z]
--include-quote-posts={BOOL}     [default true]
--include-reposts={BOOL}         [default true]
--scrape-reactions={BOOL}        [default false; opt-in only, charges extra per post]
--scrape-comments={BOOL}         [default false; opt-in only, charges extra per post]
--max-reactions={N}              [default 5; 0 = unlimited (asymmetric with --max-posts: 0)]
--max-comments={N}               [default 5; 0 = unlimited]

Validation rules (before §1.0):

  • --source-urls, --raw-output-dir, and --max-posts mandatory. If any missing, STOP and report which.
  • --source-urls must parse as non-empty JSON array of strings. Else reject (source-urls-malformed).
  • Each URL must be valid HTTP(S) with host ending in linkedin.com. First failing URL → STOP and report (source-urls-malformed).
  • --raw-output-dir must be absolute. Reject relative paths (caller owns path resolution).
  • --max-posts must parse as integer ≥ 1. Zero rejected per §6.0 max-posts-zero, Actor treats maxPosts: 0 as literal zero (returns no posts), not unlimited.

If any validation fails, STOP and report which field failed.

Read the full file on GitHub · 419 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. 11d ago First seen · 419 lines · 35 tokens per session scan A 54840414ef15

Subscribe to this mod's changes

research-crawl-linkedin-posts is a skill published in the GitHub repository thangnguyenworkspace/industry-pulse (4 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 6,783 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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