agentsclimarketplace

Capital allocation judge

Skill build-with-dhiraj/ai-workflow-framework-portability-kit/Skills/capital-allocation-judge

Portable, self-contained snapshot of a complete Claude Code setup — 36 specialist agents, 134 skills, plugins, MCP servers & host tooling. Clone, claude login, run one script, restore the whole orchestration stack in ~20 min.

Install
npx -y skills add build-with-dhiraj/ai-workflow-framework-portability-kit --skill capital-allocation-judge

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when assessing how well a CEO/management team allocates capital — to score the CONVICTION dimension "management quality" with a structured, cross-CEO scorecard drawn from William Thorndike's Outsiders framework. Applies during Stage 1 dossier writing, Stage 3 conviction re-grade, and any ad-hoc "is this management great at capital allocation?" question. The Munger/Buffett binding CIO already carries Buffett's own allocation wisdom — this skill ADDS the cross-CEO Outsiders methodology: per-share-value as the CEO scoreboard, opportunistic (not programmatic) buybacks, FCF/owner-earnings over GAAP, centralized capital + decentralized ops, leverage matched to cash-flow predictability, and contrarian analytical discipline. Triggers: "capital allocation", "how does management deploy FCF", "are buybacks value-accretive", "Outsiders framework", "management scorecard", "owner-operator quality", grading mgmt in any v2 conviction step.

SKILL.md

15.7 KB, as published. Nobody here has run it

Capital-Allocation Judge (the finance-desk "Outsiders analyst")

The v2 conviction rubric scores management quality as part of the conviction grade, but gives no structured method for how to read a management team's capital-allocation discipline. This skill encodes the Thorndike Outsiders cross-CEO scorecard as a reusable procedure. Ground every judgment in the canon (below) — never free-hand a management grade.

The binding Munger/Buffett vault remains the FINAL CIO. This skill supplies the scorecard and method; the vault supplies the judgment (moat, owner-alignment, integrity) and the verdict. Both must clear before conviction rises above 3.

STEP 0 — Pull the canon (binding-safe)

The method now lives in two layers: the Thorndike Outsiders canon atomics (tagged role=capital-allocation) AND the 30 external perspective voices that richly cover the India reinvestment-runway question (Raamdeo QGLP, Saurabh Mukherjea capital-discipline, Terry Smith, Manish Gupta, the Tambade asset-light lens). Do a dual-pull and union the slugs:

# (a) BINDING — the CIO ranking and arbiter (run ALWAYS; these atoms are the verdict)
set -a && source /Users/Dhiraj/dev/invest/.env && set +a && /Users/Dhiraj/dev/invest/.venv/bin/python \
  /Users/Dhiraj/dev/invest/data/scripts/32_consult_brain.py \
  --corpus binding --step capital-allocation \
  --company "<company> capital allocation owner earnings reinvest above cost of capital buybacks dividends" \
  --model general --json-out extracted/grilling/<TICKER>_capalloc_binding.json

# (b) PERSPECTIVES — the India runway voices (context/divergence only, NEVER the verdict)
set -a && source /Users/Dhiraj/dev/invest/.env && set +a && /Users/Dhiraj/dev/invest/.venv/bin/python \
  /Users/Dhiraj/dev/invest/data/scripts/32_consult_brain.py \
  --corpus perspectives --step capital-allocation --k 15 \
  --company "<company> reinvestment runway incremental ROCE QGLP asset light capital discipline long runway" \
  --model general --json-out extracted/grilling/<TICKER>_capalloc_persp.json

cites_principles ⊂ the union of returned slugs.

Retrieval wiring (the fix landed — read this). A dedicated --step capital-allocation now exists, and --role is now INCLUSIVE. But there is a lossy trap that runs opposite to the old warning: the Thorndike canon atoms are tagged role=capital-allocation, the 30 external voices are NOT. So --role capital-allocation filters to the academic-canon layer and hides the India runway perspectives. Do NOT lead with --role capital-allocation. Use the dual-pull above: --corpus binding for the CIO ranking, and --corpus perspectives with NO --role to surface the external voices. (--corpus blended also surfaces the desk-synthesis atomics below alongside the binding layer — use it when you want both in one call.)

  • Score the perspectives layer evidence-gated — credit a long runway only on actual incremental ROCE history, never on a projected TAM narrative. The perspectives are promotional (managers and newsletter writers talking their book), so they are context and divergence-detection, never the verdict.
  • ABSTAIN on any axis whose atom the consult does not return — do not assign a non-zero score on an axis you could not ground. Thin retrieval ⇒ lower the grade, never fabricate the slug.

THE BINDING PRIOR (what the CIO already holds)

Before the scorecard, anchor to the CIO's own allocation ranking — the scorecard measures HOW WELL management executes against this prior, not WHETHER the prior is right. The binding order of preference, from [[owner-earnings-and-capital-allocation-as-intrinsic-value-engine]]:

reinvest above cost of capital > buy back stock when cheap > tax-efficient buyback > dividend

([[prefer-buybacks-over-dividends-for-tax-efficiency]], [[seek-companies-with-strong-capital-return]].) This ranking is the binding prior; the six-axis scorecard below grades execution quality against it. The Munger/Buffett CIO remains the arbiter — a high scorecard cannot override the binding veto on a business that must constantly reinvest just to stand still ([[avoid-businesses-requiring-constant-reinvestment]]).

WHY this scorecard (the core insight)

The Outsiders CEOs outperformed the S&P 500 by ~20× over their tenures — not by being the best operators, but by being the best capital allocators. Thorndike's lens: the CEO is first and foremost a capital allocator; operational excellence matters, but FCF + what management does with it is what compounds per-share value. GAAP earnings are a distraction. The eight Outsider CEOs shared five structural traits (the scorecard below).

THE SCORECARD — six axes, rate each 0 / 1 / 2

(Axes 1–5 are the Thorndike Outsiders style traits; Axis 6 adds the literal compounding driver — incremental ROCE × runway — so the scorecard grades the economics, not just the style.)

Run through each axis for the company under review. Use only evidence from the dossier, annual reports, and canon-returned principles. Never infer a high score without evidence.

Axis 1 — Per-share value as the CEO scoreboard

Canon slug: per-share-value-optimization

Score 2: Management explicitly tracks per-share owner-earnings growth (not total PAT / revenues / market cap) as the primary internal metric; discusses reinvestment decisions in terms of their per-share IV impact; resists accretive-to-EPS dilutive raises. Score 1: Some awareness of per-share metrics but mixes with revenue/headcount growth language. Score 0: Management scorecard is total profit, EBITDA, revenue, or market cap — not per-share value.

Axis 2 — FCF / owner-earnings over GAAP

Canon slugs: cash-flow-over-earnings, cash-flow-over-earnings-metric

Score 2: Management consistently discusses FCF or owner-earnings (not GAAP net income or EBITDA) in communications; capex and reinvestment are laid out explicitly; the income statement is secondary to the cash flow statement in how they talk to investors. Score 1: FCF mentioned alongside GAAP; some explicit capex vs maintenance distinction. Score 0: Communication anchored to PAT/EBITDA; FCF treated as incidental.

Axis 3 — Value-accretive deployment OR disciplined non-deployment

Canon slugs: buybacks-when-cheap, opportunistic-buybacks-vs-programmatic Desk/binding: [[capital-light-vs-capital-heavy-allocation-is-not-a-style-score]], [[holding-cash-is-a-deliberate-allocation-choice]], [[capital-light-moats-perform-best-in-inflation]], [[avoid-businesses-requiring-constant-reinvestment]]

This axis credits value-accretive action OR disciplined inaction — do NOT penalise an asset-light compounder for low capex. Three Score-2 paths:

  • (i) Opportunistic deployment: buybacks / acquisitions / aggressive organic reinvestment in large, irregular blocks when price is demonstrably below IV — then nothing for long periods; management can articulate why the price was cheap.
  • (ii) Capital-light high-ROC: the business reinvests little yet earns high ROC and returns the rest — low capex is the feature, not a deployment failure ([[capital-light-vs-capital-heavy-allocation-is-not-a-style-score]]; [[capital-light-moats-perform-best-in-inflation]]).
  • (iii) Deliberate cash-holding: management holds cash on purpose to await sub-IV prices ([[holding-cash-is-a-deliberate-allocation-choice]]) — credited ONLY when paired with documented sub-IV opportunity-awareness AND an above-cost-of-capital core business.

Score 1: Some evidence of price-sensitivity in buybacks/M&A, OR capital-light economics without a clear return-of-cash record. Score 0: Programmatic steady-state buybacks regardless of price; acquisitions driven by growth narrative / peer pressure; consistent over-payment for M&A; or idle cash hoarded in a mediocre (below-cost-of-capital) business — that is empire-protection, not discipline, and scores 0.

Axis 4 — Centralized capital + decentralized operations

Canon slug: centralized-capital-decentralized-ops

Score 2: Capital allocation authority sits with the CEO / board (not diffused to divisional heads); operating decisions are pushed to the business unit or branch level; HQ is lean. Score 1: Partial centralization — some capital decisions decentralized or locked in budgets. Score 0: Capital decisions fragmented across divisions; headquarters is bureaucratic; operating autonomy low.

Axis 5 — Leverage matched to cash-flow predictability + contrarian discipline

Canon slugs: leverage-matched-to-predictability, leverage-predictability-test, contrarian-analytical-discipline, contrarian-analytical-temperament

Score 2: Debt (if any) is sized to the predictability of recurring cash flows and stress- tested through economic cycles; management can quantify the FCF cushion. Capital decisions are rooted in independent quantitative analysis, not peer benchmarking or analyst consensus. Score 1: Leverage moderate with some stress-test evidence; or contrarian actions documented but not quantitatively grounded. Score 0: Leverage sized to optimism/guidance, not to cycle-adjusted FCF; or management consistently follows the herd on capital deployment.

Axis 6 — Reinvestment runway × incremental ROCE (the compounding driver)

Desk: [[reinvestment-runway-as-the-sixth-allocation-axis]]

The five style axes measure how management allocates; this axis measures the literal compounding economics — incremental ROCE × length of runway — which is what actually drives per-share value. Score it on realised incremental ROCE history, never a projected TAM narrative (the perspectives layer is promotional; this axis is evidence-gated).

Score 2: High incremental ROCE (>~18–20%; Raamdeo's >15% ROE floor as a minimum, Terry Smith's ~30% as the aspiration) AND a demonstrably long runway — large under-penetrated TAM, QGLP "Longevity", reinvestment opportunity not yet exhausted. Score 1: Solid incremental ROCE but a maturing / partly-penetrated runway; OR a long runway at only moderate incremental returns. Score 0: Incremental ROCE near the cost of capital (reinvestment is not compounding value), OR the runway is nearly exhausted (high ROC with nowhere left to deploy → the engine is stalling).

SCORING + CONVICTION FEED

Sum the six axes (max = 12):

TotalCapital-allocation gradeConviction feed
11–12Outsider-class (rare)+1 to conviction (subject to moat gate)
8–10Strong allocatorSupports conv 4–5 if moat present
6–7Adequate / mixedNeutral; does not lift or cap
4–5Weak allocator−1 to conviction ceiling
0–3Capital destroyerCap conviction at 2 regardless of moat

Gates still bind:

  • No moat → conviction cap 1, regardless of allocation score.
  • Chronically weak/near-zero FCF → conviction cap 2, regardless of allocation score.
  • ROIC below ~12% cost of capital → conviction cap 2.
  • An Outsider-class score in a commoditized or moat-free business is not a pass — great allocation of bad economics still compounds mediocre results.

OUTPUT (feeds Stage 3 / conviction re-grade)

Return a structured block:

capital_allocation_scorecard:
  per_share_value:        [0|1|2] — <evidence sentence>
  fcf_over_gaap:          [0|1|2] — <evidence sentence>
  value_accretive_deploy: [0|1|2] — <evidence sentence (deployment OR disciplined non-deployment)>
  centralized_capital:    [0|1|2] — <evidence sentence>
  leverage_contrarian:    [0|1|2] — <evidence sentence>
  reinvestment_runway:    [0|1|2] — <incremental-ROCE × runway, realised history not TAM>
  total:                  [0–12]
  grade:                  [Outsider-class | Strong | Adequate | Weak | Destroyer]
  conviction_feed:        [+1 | supports 4-5 | neutral | -1 | cap 2]
  cites_principles:       [slugs returned by the consult ONLY]
  cites_moat:             [moat-gate link — seek-enduring-moats / moat-reinvestment-opportunity-valuation-integration]
  cites_valuation_link:   [reinvestment-rate-terminal-value-consistency — the g = reinvest-rate × ROC identity feeds DCF terminal value]
  portfolio_mirror:       [opportunity-cost-and-capital-allocation — this name's allocation vs the portfolio's best alternative use of capital]
  allocation_kill_criteria: <one sentence — what would prove the grade wrong>

Embed this block in the dossier's "Capital Allocation" section and carry conviction_feed forward into the Stage 3 structured output. The three horizontal edges make the dossier explicitly carry allocation into (a) the moat gate ([[seek-enduring-moats]], [[moat-reinvestment-opportunity-valuation-integration]]), (b) the DCF terminal value — runway × incremental ROCE is the g = reinvestment-rate × ROC identity ([[reinvestment-rate-terminal-value-consistency]]), and (c) portfolio sizing ([[opportunity-cost-and-capital-allocation]]).

Hard rules

  1. Never assign Outsider-class (11–12) without documentary evidence on all six axes. Narrative framing from management IR is not evidence — look for actions (actual buyback timing, deal multiples, capex decisions vs guidance, realised incremental ROCE) not words. Axis 6 in particular must rest on realised incremental-ROCE history, never a projected TAM.
  2. Always cite only canon slugs the consult actually returns. If principles comes back empty / thin on Thorndike atomics, flag it and score conservatively.
  3. The allocation grade feeds conviction but does NOT override the moat gate. A conv 1 (no moat) stays at 1 regardless of allocation score.
  4. The Munger/Buffett binding CIO remains the arbiter of moat / verdict / margin-of-safety. This skill supplies the capital-allocation number inside conviction; it does not issue verdicts.
  5. Indian listed companies rarely have Axis 3 (buyback) evidence — but Axis 3 now also credits capital-light high-ROC economics and deliberate sub-IV cash-holding, so do not auto-score it 0 for a low-capex compounder. Still score 0 for a routine buyback programme (not opportunism) and for idle cash hoarded in a below-cost-of-capital business.
  6. The perspectives layer is context, never the verdict. The dual-pull surfaces 30 external voices (Raamdeo, Mukherjea, Terry Smith, Tambade) who talk their book and frequently agree with each other — they can inform Axis 6 and flag divergence, but they may NEVER override the binding Munger/Buffett CIO on temperament, moat, verdict, or MoS. Always run the separate --corpus binding call; its atoms are the arbiter. A glossy "long runway" narrative does not lift conviction without realised incremental-ROCE evidence, and the binding veto ([[avoid-businesses-requiring-constant-reinvestment]]) sits above the whole scorecard.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.