Borrowing it
Nothing to install: this file belongs to tusharagg1/aifolimizer. 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/tusharagg1/aifolimizer/master/.claude/skills/tax-loss-review/SKILL.mdgit clone --depth 1 https://github.com/tusharagg1/aifolimizerWrote 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/skills/tusharagg1/aifolimizer/tax-loss-review)<a href="https://agentmods.dev/skills/tusharagg1/aifolimizer/tax-loss-review"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/tax-loss-review/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/skills/tusharagg1/aifolimizer/tax-loss-review"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/tax-loss-review.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 | $0.00051 | $0.00738 |
| Opus 5 | $0.00026 | $0.00369 |
| Sonnet 5 | $0.00010 | $0.00148 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
tax-loss-review 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 11d 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 — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tax-Loss Harvesting Review (Canadian rules)
How to run
- Call
mcp__aifolimizer__get_profile- identify which account holds each position (TFSA/RRSP losses NOT deductible) - Call
mcp__aifolimizer__get_personal_context- usederived.marginal_tax_rate_pct+ province to compute each loss's after-tax value (loss × 50% inclusion × marginal rate), so picks are ranked by real tax savings not gross loss. Ifpresent=false, mark the dollar value as an estimate and suggest running profile-setup. - Call
mcp__aifolimizer__get_tax_loss_candidateswith threshold_pct=-5.0 (or stricter -10.0 for clearer picks) - For each candidate, check account placement matters for tax
Key Canadian rules to enforce
- TFSA / RRSP / FHSA losses are NOT deductible - only non-registered accounts qualify
- Superficial loss rule (30 days): if you (or spouse) buy back same security or "substantially identical" one within 30 days before or after sale, loss is denied
- Capital losses in non-registered accounts offset capital gains (current year, carry back 3 years, carry forward indefinitely)
- Substitute trades: typically different but similar ETF (e.g., sell VFV → buy XUS as non-identical S&P 500 proxy) - though "substantially identical" is judgment
Output structure
- Account-by-account breakdown - tax-loss-eligible (non-reg) vs not (TFSA/RRSP/FHSA)
- Ranked list of eligible loss candidates by unrealized loss size
- Per top candidate: ticker, unrealized loss $, %, suggested substitute ETF
- Superficial loss warnings: candidates conflicting with recent buys
- Total deductible loss vs total realized gains YTD (ask user if unknown)
- Action plan: sell list, reinvest list, calendar (avoid 30-day window)
Rules
- Under 400 words
- Never recommend selling TFSA/RRSP position for tax reasons
- Always flag 30-day superficial loss risk
- Suggest substitutes avoiding "substantially identical" designation
Gotchas
- Superficial loss rule covers user AND spouse/common-law partner AND any controlled corp - ask before assuming buy-back window is clean.
- 30-day window is 30 calendar days BEFORE and AFTER sale - both sides count.
- Same-class ETFs tracking same index (e.g. VFV ↔ VOO) likely "substantially identical" per CRA - recommend different index proxy (e.g. VFV → XUS uses different index methodology, safer).
- TFSA losses are PERMANENT - contribution room not restored. Mention when discussing TFSA exits.
- USD-denominated cost basis must be converted at transaction-date FX rate, not current -
get_tax_loss_candidatesmay show CAD-converted loss that misstates actual ACB. Flag and recommend user verify with broker statement. - Capital losses cannot offset interest/dividend income - only capital gains. Don't suggest harvesting to "offset T5 income".
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.
- 11d ago First seen · 46 lines · 51 tokens per session scan A 91dbfcee9dc0
tax-loss-review is a skill published in the GitHub repository tusharagg1/aifolimizer (1 stars, last pushed 10d ago), licensed MIT. It adds 51 tokens to every session and 738 once invoked, about $0.0003 per session on Opus 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 skills, from other repositories
quantoracle
63 deterministic quantitative finance calculators + 10 composite workflows via MCP. Options pricing, Greeks, exotic derivatives, risk metrics, portfolio optimization, Monte Carlo, statistics, crypto/DeFi, FX/macro, TVM, strategy backtesting, rebalance planning, options strategy selection, hedging. 1,000 free…
gitee-expert
You have access to Gitee (gitee.com), China's largest GitHub-style platform. This skill teaches the effective workflows for discovery, intel, translation and webhook monitoring.
transcribe-filing
Transcribe an insurance rate filing or internal rating manual into an OpenRater workbook, then validate, build, verify, and rate it through the OpenRater MCP tools. Use when the user shares a filing/manual (PDF or pages) and wants it executable — "build this filing", "digitize this rating manual", "make this rateable"…
tushare
A Python interface for Tushare, a financial data service that provides market and company information for stocks, funds, futures, and digital assets. It returns queried data as pandas tables.
social-media-intelligence
Social media intelligence: financial signal extraction from Twitter/X, Telegram, Discord, and Reddit for sentiment-driven trading strategies.
geopolitical-risk
Geopolitical risk analysis: quantify crisis signals, identify precursors, and build event-driven strategies for war, sanctions, and supply disruption scenarios.