Agentic Capacity Compass — Development skill for Claude Code
Agentic workforce planning tool — analyzes staffing levels, vacancies, workload, productivity, and anticipated departures across divisions, recommends specific staffing allocations, and simulates the.
How to install Agentic Capacity Compass
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open JustinLaSalle/Agentic-Capacity-Compass and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Agentic Capacity Compass does
Agentic workforce planning tool — analyzes staffing levels, vacancies, workload, productivity, and anticipated departures across divisions, recommends specific staffing allocations, and simulates the impact of FTE losses, workload spikes, or automation.
Alternatives in Development
- Sprint Plan — Plan sprints with capacity, story selection, and risk mapping 7.8k ★
- Codexmcp — Enable seamless collaboration between Claude Code and Codex, transforming from a single agent to multiple agen 2k ★
- Compass Planner — Use the @compass-planner agent to help the user create a work plan for the following: $ARGUMENTS 523 ★
README
Capacity Compass
An agentic workforce planning tool — analyzes staffing levels, vacancies, workload, productivity, and anticipated departures across divisions, recommends specific staffing allocations, and simulates the impact of FTE losses, workload spikes, or automation. Built with the [Claude API](https://docs.claude.com).
Live demo
**[Try it here](https://claude.ai/artifact/XQitELSonn8ekGzkeNqQjK)** — note: trying the interactive AI recommendation and simulation features requires a free Claude account to sign in with (a platform requirement for any page that calls Claude live, not specific to this project). The editable staffing table and live metric calculations work without an account.
The problem
Staffing decisions — where to reallocate headcount, which vacancies are most urgent, what happens if a division loses people or workload spikes — usually require pulling data from several places and doing the math by hand before anyone can even start reasoning about what to do. This project separates those two steps cleanly: real arithmetic computed deterministically from the actual numbers, and an AI layer used for what it's actually good at — reasoning across that data and producing a specific, named recommendation, not vague advice.
What it does
**Current Staffing** — an editable table of divisions, each tracking budgeted FTE, filled FTE, vacancies, monthly workload volume, productivity per FTE, and anticipated departures over the next 12 months. Every division's **required FTE, staffing gap (short/surplus/balanced), and utilization percentage are computed live and client-side** as you edit — never left to the AI to estimate. An org-wide summary rolls these up across every division. A "Get staffing allocation recommendations" button has the AI review the real computed numbers and recommend specific moves — which named division is overstaffed relative to workload, which named division needs urgent backfill, and why the anticipated departures chang
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