Install
openclaw skills install @mohitagw15856/capital-allocationAllocate a finite budget or headcount across competing initiatives by return and strategic fit. Use when asked to allocate budget, decide where to invest, build a funding/portfolio plan, or make trade-offs across initiatives under a cap. Produces a capital-allocation plan — initiatives scored by expected return × strategic fit per dollar, a funded/unfunded split against the cap, the cut line, and the reasoning.
openclaw skills install @mohitagw15856/capital-allocationAllocating capital is the core executive job: a fixed pot, more good ideas than money, and the need to say no on the record. This skill scores initiatives by expected return and strategic fit per unit of cost, allocates against the cap (honouring must-funds), and makes the cut line explicit — so funding is a defensible portfolio choice, not the loudest voice in the room.
Ask for these only if they aren't already provided:
1. Objective & cap — what you're optimising and the total available.
2. Scored initiatives — a table; score = expected value × strategic fit, normalised per unit cost:
| Initiative | Cost | Expected return | Strategic fit (1–5) | Score / $ | Must-fund? |
|---|
3. The allocation — funded vs. unfunded against the cap, with budget utilisation. Must-funds first, then highest score/$ until the cap binds.
4. The cut line — the marginal initiative that just missed, and what it would take to fund it (the most useful number for the debate).
5. Rationale & trade-offs — why the portfolio is balanced this way, what's deliberately not funded, and the reversibility of each bet.
6. Re-evaluation triggers — what would change the allocation mid-period (a bet pays off early, a must-fund grows).
scripts/capital_allocate.py (stdlib only) does the allocation deterministically — must-funds first, then
by score-per-cost until the cap binds — and reports the cut line:
# items.json: [{"name":"Mobile revamp","cost":300,"expected_return":900,"strategic_fit":5,"must_fund":false}, ...]
python3 scripts/capital_allocate.py items.json --budget 1000
python3 scripts/capital_allocate.py items.json --budget 1000 --json
Portfolio capital-allocation practice — expected-value × strategic-fit scoring per unit cost, against a hard constraint.