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/trading-desk/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/trading-desk)<a href="https://agentmods.dev/skills/tusharagg1/aifolimizer/trading-desk"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/trading-desk/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/trading-desk"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/trading-desk.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 | $0.00094 | $0.01081 |
| Opus 5 | $0.00047 | $0.00541 |
| Sonnet 5 | $0.00019 | $0.00216 |
| Haiku 4.5 | $0.00009 | $0.00108 |
Grade A, and why
trading-desk 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 10d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trading Desk (Analyst → Research → Risk → PM Gate → Execution)
Goal
One orchestrated pass that mirrors an institutional desk: independent analysis, adversarial debate, portfolio-level risk check, behavioral discipline gate, and a final Portfolio-Manager decision that GATES whether a trade ticket is emitted. No single stage can wave a trade through. Output ends in APPROVE + ticket or REJECT + reasons - never a ticket on reject.
When to invoke
- User wants the complete process on a name before real capital
- A high-conviction idea needs a disciplined second look
- Before any position-sized entry (not a quick quote check)
Pipeline (run in order; each stage can veto)
Stage 0 - Mandate (REQUIRED):
mcp__aifolimizer__get_profile- capital, account types (never hardcode)mcp__aifolimizer__get_ticker_decision_history(ticker=TICKER, max_decisions=5) +mcp__aifolimizer__get_ticker_reflection(symbol=TICKER, n=3) +mcp__aifolimizer__get_cross_ticker_lessons(max_lessons=3) - load prior decisions BEFORE the desk forms a view. If a prior decision exists and this run flips it, the PM must state explicitly WHY (new data / catalyst / price); never silently contradict a logged decision.- Confirm ticker, direction (BUY/ADD/TRIM/SELL), horizon, rough size. If the user can't state a thesis, stop here (REJECT: no thesis).
Stage 1 - Analyst + adversarial research:
- Run the
adversarial-researchskill (bull / bear / consensus) on the ticker. - Capture: fair-value estimate, key bull driver, key bear risk, base-rate.
- For US names, fold in
mcp__aifolimizer__get_dcf_valuationas a quantitative fair-value anchor.
Stage 2 - Risk gate (HARD veto):
mcp__aifolimizer__get_risk_gate_state- if BUYs are halted (drawdown / VIX / loss-streak), a BUY/ADD is auto-REJECTED regardless of conviction.mcp__aifolimizer__get_positioning_signals- crowding ≥70 on a BUY/ADD = veto (defer; negative expected alpha for late entries).mcp__aifolimizer__get_concentration_warnings- if this trade breaches single-name/sector limits, veto or force size-down.
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.
- 10d ago First seen · 78 lines · 94 tokens per session scan A 79ca89e6bcb7
trading-desk is a skill published in the GitHub repository tusharagg1/aifolimizer (2 stars, last pushed 9d ago), licensed MIT. It adds 94 tokens to every session and 1,081 once invoked, about $0.0005 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.
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