recruit-employer

recruit-employer is a skill for Claude Code, Codex from tal7aouy/RecruitKit. It costs 33 tokens per session (2,450 once invoked), scanned A, a copy of recruit-employer, MIT.

An employer-brand audit that reviews how a company appears to job candidates across review sites, professional networks, its careers site, press, and employee feedback.

In plain words
What is it for?
It helps assess sources such as Glassdoor, Indeed, LinkedIn, Blind, and the careers site, then compare perceptions with competing employers and identify recruiting-brand issues.
Why use it?
It brings scattered public impressions together so recruiting teams can see whether the company’s reputation is helping or hurting applications.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps assess sources such as Glassdoor, Indeed, LinkedIn, Blind, and the careers site, then compare perceptions with competing employers and identify recruiting-brand issues.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tal7aouy/recruitkit/recruit-employer
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 tal7aouy/RecruitKit --skill recruit-employer
Clone the repo
git clone --depth 1 https://github.com/tal7aouy/RecruitKit

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 recruit-employer

README.md
[![agentmods](https://agentmods.dev/badge/skills/tal7aouy/recruitkit/recruit-employer/github.svg)](https://agentmods.dev/skills/tal7aouy/recruitkit/recruit-employer)
Your own site
<a href="https://agentmods.dev/skills/tal7aouy/recruitkit/recruit-employer"><img src="https://agentmods.dev/badge/skills/tal7aouy/recruitkit/recruit-employer/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 recruit-employer

Your own site · 80×15
<a href="https://agentmods.dev/skills/tal7aouy/recruitkit/recruit-employer"><img src="https://agentmods.dev/badge/skills/tal7aouy/recruitkit/recruit-employer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,450 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 94% 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 $0.00033 $0.02450
Opus 5 $0.00016 $0.01225
Sonnet 5 $0.00007 $0.00490
Haiku 4.5 $0.00003 $0.00245

Measured 11d ago against content hash 4d7f08005668, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

recruit-employer 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.

Origin

This is a copy

94% identical to recruit-employer — 4 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.

skills/recruit-employer/SKILL.md · 318 lines

How it starts

The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Employer Brand Audit

You are the Employer Brand engine for the RecruitKit. When invoked with /recruit employer <company>, you audit how candidates perceive this company across all the surfaces they research before applying (Glassdoor, Indeed, LinkedIn, Blind, career site, press). The goal: a clear-eyed view of whether the company's brand is helping or hurting the recruiting funnel — and what to do about it.

DISCLAIMER: For educational/research purposes only. AI-generated analysis based on publicly available data. Always verify with HR / talent leadership before acting.


TRIGGER

  • /recruit employer <company> — audit a company
  • Also: "employer brand for [company]", "Glassdoor analysis", "candidate perception"

INPUT PROCESSING

  1. Confirm:
    • Company name
    • Industry
    • Company stage (startup / growth / public / enterprise)
    • Career site URL
    • Recent news context (layoffs, fundraises, leadership changes)
  2. Pull publicly available data via WebSearch

EXECUTION PIPELINE

STEP 1: Aggregate Review Data

Pull from:

Platform Pull
Glassdoor Overall rating, review count, CEO approval, recommend %, recent reviews
Indeed Overall rating, review count, work happiness score
LinkedIn Follower count, follower growth, employee count change, leadership posting
Blind Sentiment threads (if accessible)
Comparably Culture scores by dimension
Reddit / forums Industry-specific subreddits and groups

STEP 2: Theme Extraction

Top 5 positives + top 5 negatives from recent reviews (last 12 months):

Top Positives:

  1. [Theme + frequency + quote example]
  2. ...

Top Negatives:

  1. [Theme + frequency + quote example]
  2. ...

Common positive themes: smart coworkers, mission, learning, flexibility, comp, growth Common negative themes: long hours, comp gap, unclear promotion, leadership churn, layoffs, politics

STEP 3: Career Site Audit

Score the career site on:

Dimension Check
Mobile responsive Test on phone
Employee stories Day-in-life content present?
Values articulated Specific (not "we love teamwork")
Benefits detailed Beyond bullet list
DEI commitment Specific metrics, not generic statement
Team photos Real, not stock
Application UX Fewer than 10 clicks to apply
Diversity in imagery Reflects target candidate diversity
Search/filter Roles searchable by team, location
EEO statement Visible, current

Read the full file on GitHub · 318 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 · 318 lines · 33 tokens per session scan A 4d7f08005668

Subscribe to this mod's changes

recruit-employer is a skill published in the GitHub repository tal7aouy/RecruitKit (3 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 2,450 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to recruit-employer, differing in 4 lines, and is treated as a copy.

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