competitive-intel: Agent for Claude Code

.claude/agents/linkedin-researcher.md

linkedin-researcher is an agent for Claude Code from brittanyslay/competitive-intel. It costs 47 tokens per session (690 once invoked), scanned A, original, no licence file.

A research agent for finding and analyzing LinkedIn posts published by competitors. It identifies recurring messages, product signals, and changes in tone.

In plain words
What is it for?
Use it to study competitor messaging, notice product announcements or signals, and track changes in communication style.
Why use it?
It removes the need to manually search many competitor posts and compare what they are saying over time.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is brittanyslay/competitive-intel's own configuration. It tells Claude Code how to work on competitive-intel 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 competitive-intel configures →

Reuse

Borrowing it

Nothing to install: this file belongs to brittanyslay/competitive-intel. 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/brittanyslay/competitive-intel/main/.claude/agents/linkedin-researcher.md
Clone the repo
git clone --depth 1 https://github.com/brittanyslay/competitive-intel

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 linkedin-researcher

README.md
[![agentmods](https://agentmods.dev/badge/agents/brittanyslay/competitive-intel/linkedin-researcher/github.svg)](https://agentmods.dev/agents/brittanyslay/competitive-intel/linkedin-researcher)
Your own site
<a href="https://agentmods.dev/agents/brittanyslay/competitive-intel/linkedin-researcher"><img src="https://agentmods.dev/badge/agents/brittanyslay/competitive-intel/linkedin-researcher/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-researcher

Your own site · 80×15
<a href="https://agentmods.dev/agents/brittanyslay/competitive-intel/linkedin-researcher"><img src="https://agentmods.dev/badge/agents/brittanyslay/competitive-intel/linkedin-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 690 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 unknown 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 $0.00047 $0.00690
Opus 5 $0.00023 $0.00345
Sonnet 5 $0.00009 $0.00138
Haiku 4.5 $0.00005 $0.00069

Measured 7d ago against content hash 656dceca9f4b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

linkedin-researcher 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 7d 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/agents/linkedin-researcher.md · 70 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

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. 7d ago First seen · 70 lines · 47 tokens per session scan A 656dceca9f4b

Subscribe to this mod's changes

linkedin-researcher is an agent published in the GitHub repository brittanyslay/competitive-intel (0 stars, last pushed 17d ago), with no licence file. It adds 47 tokens to every session and 690 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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