Borrowing it
Nothing to install: this file belongs to haiiibin/claude-multi-agent-investing. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/haiiibin/claude-multi-agent-investing/main/.claude/commands/allocate-cash.mdgit clone --depth 1 https://github.com/haiiibin/claude-multi-agent-investingWrote 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.
[](https://agentmods.dev/commands/haiiibin/claude-multi-agent-investing/allocate-cash)<a href="https://agentmods.dev/commands/haiiibin/claude-multi-agent-investing/allocate-cash"><img src="https://agentmods.dev/badge/commands/haiiibin/claude-multi-agent-investing/allocate-cash/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.
<a href="https://agentmods.dev/commands/haiiibin/claude-multi-agent-investing/allocate-cash"><img src="https://agentmods.dev/badge/commands/haiiibin/claude-multi-agent-investing/allocate-cash.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.02435 |
| Opus 5.5 | $0.00015 | $0.00974 |
| Sonnet 5.5 | $0.00007 | $0.00487 |
| Haiku 4.5 | $0.00004 | $0.00244 |
Grade A, and why
allocate-cash 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/allocate-cash -- Cash Deployment Strategy
Portfolio construction exercise: given cash + current exposures + regime, what to buy and where. Not a single-ticker recommendation.
Input
- Default: read
holdings.json(cash fields + holdings) $ARGUMENTScan override: e.g.,deploy 60% of cash, hold 40% reserveor explicit cash amounts
If input is ambiguous, ask ONE targeted question, then proceed.
Phase 1 -- Audit
Journal pre-scan: Read memory/long_term/journal.md (if exists). Filter last 30 days. Extract:
- "waiting for {TICKER} at {price}" entries → if current price has crossed trigger, surface as automatic Tier 1 candidate
- "passed on {TICKER}" entries → note why, don't re-recommend without new evidence
- "thesis-change on {TICKER}" entries → surface as candidate to trim
- Prepend a 3-bullet summary to Phase 4 candidate generation context
Watchlist sanity check: for each entry in holdings.json watchlist[]:
- Pull
get_stock_info(ticker).currentPrice - Parse the
notefield for direction keywords:< $X/> $X/below X/above X - If
notesays "waiting for < $X" butcurrent > X × 1.5(target is 50%+ under current), emit⚠️ {ticker}: target $X is {gap}% below current $Y -- check if target is stale (split? old thesis?) - Same for inverse: note says
> $Xbut current is already well above - Don't block; just surface. User fixes the note or removes the entry.
This catches dead watchlist entries from stock splits or thesis drift (e.g. GOOGL target < $180 after the 20:1 split in 2022 when the note was written pre-split).
Read holdings.json. Compute:
Totals: MV per account (native + base currency), cash per account/currency, cash % of portfolio.
Concentration -- aggregate by TICKER across accounts (not by row). Same ticker in 2 accounts = 1 position. Report top 5 aggregate positions.
Data integrity check: for each holding, sanity-check cost_basis vs 5y price range. Flag if >2× 5y_high or <0.5× 5y_low → likely stale from split (see CLAUDE.md). Do not compute P&L on flagged positions.
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.
- 2mo ago First seen · 167 lines · 37 tokens per session scan A e192988f442d
allocate-cash is a command published in the GitHub repository haiiibin/claude-multi-agent-investing (2 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 2,435 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
tax-sanity
Tax awareness sanity-check (NOT tax advice). Walks through entity tax-efficiency, deductions, growth structure, quarterly estimateds, multi-jurisdiction, retirement/long-term questions. Produces a Tax Readiness Checklist for the person's meeting with their accountant.
model-revenue
Produce a Revenue Model — current revenue map by stream, target revenue map, concentration risk flags, margin analysis, unit economics, growth-curve shape per stream, compounding-vs-linear assessment. Composes with Genius Profile Freedom Path buckets. Not financial advice.
portfolio
View TastyTrade portfolio summary (positions and balances).
pm-pricing
Author or refresh a pricing plan — 2–3 monetization models with willingness-to-pay rationale per audience. Spawns pricing-strategist.
pm-burn
Cost burn-rate — LLM cost over the last N days vs a human-equivalent baseline (savingsx). Flags cost outliers and abnormal-burn agents.
sages
Summon the Market Sages council to analyze a stock (e.g. /sages AAPL, /sages NVDA --value).