Compensation & Salary Benchmarking
v1.0.0Build competitive compensation plans using market data, salary bands, equity, bonuses, geographic pay adjustments, and retention risk scoring.
⭐ 0· 577·1 current·1 all-time
by@1kalin
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name, description, and runtime instructions all align: the skill provides frameworks, checklists, and metrics for building compensation plans and does not request unrelated access or tools.
Instruction Scope
SKILL.md is self-contained and describes how to build salary bands, audits, and retention scoring. It references external data sources (Levels.fyi, Glassdoor, Radford, Mercer, LinkedIn, BLS) and AfrexAI product links; this is expected for benchmarking but could lead an agent to request or aggregate employee data or to consult external services if the user supplies credentials or datasets.
Install Mechanism
No install spec or code files — this is instruction-only, so nothing is written to disk or fetched at install time.
Credentials
The skill requests no environment variables, credentials, or config paths. No disproportionate secret access is required for the stated functionality.
Persistence & Privilege
Skill is not always-on and is user-invocable; it does not request persistent agent-level privileges or modifications to other skills/configs.
Assessment
This skill appears coherent and low-risk because it is instruction-only and asks for no credentials or installs. Before installing or using it, consider: (1) avoid pasting sensitive employee PII or full payroll exports into the agent unless you trust its context and storage policies; (2) the framework references paid/third-party data sources — you will need to supply or fetch data manually (and may require subscriptions); (3) the README/SKILL.md contains promotional links to AfrexAI products — be cautious about following purchase links or sharing credit card/account info; (4) if you ask the agent to perform audits, confirm what data it will access, how it stores results, and who can see them. Overall, the skill is consistent with its stated purpose — treat it as a guidance/template tool rather than an automated data connector.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.