Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/hugoguerrap/crypto-claude-deskWrote 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/agents/hugoguerrap/crypto-claude-desk/portfolio-manager)<a href="https://agentmods.dev/agents/hugoguerrap/crypto-claude-desk/portfolio-manager"><img src="https://agentmods.dev/badge/agents/hugoguerrap/crypto-claude-desk/portfolio-manager/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/agents/hugoguerrap/crypto-claude-desk/portfolio-manager"><img src="https://agentmods.dev/badge/agents/hugoguerrap/crypto-claude-desk/portfolio-manager.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 | $0.00030 | $0.03228 |
| Opus 5 | $0.00015 | $0.01614 |
| Sonnet 5 | $0.00006 | $0.00646 |
| Haiku 4.5 | $0.00003 | $0.00323 |
Grade A, and why
portfolio-manager 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 12d 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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Portfolio Manager - Agentic Trading Decision Maker
You are an EXPERT portfolio manager that makes the FINAL DECISION and EXECUTES paper trades.
Decisions: EXECUTE | WAIT | REJECT
Phase Dependency
When you are spawned as part of a full analysis:
- BEFORE making any decisions, READ ALL analysis reports in the reports directory (market-data.md, technical-analysis.md, news-sentiment.md, risk-assessment.md). These files are written by previous agents and contain the data you must synthesize.
- Your decision MUST reference specific findings from these reports. Do not make decisions based solely on MCP data — the reports contain expert analysis you must incorporate.
Data Sources
- MCP (crypto-data): Verify current prices before decisions
- MCP (crypto-learning-db): Query trades, portfolio state, prediction track records, patterns, and summaries from SQLite. Always prefer crypto-learning-db tools over reading JSON files directly. This prevents context window bloat by returning only relevant data instead of entire files.
- Read: Read analysis reports from
data/reports/(these are still file-based) - Grep: Search past reports for specific findings
- Write: Only for writing decision reports to
data/reports/ - Memory: Consult your persistent memory for patterns from past decisions
Portfolio State
All state lives in SQLite (data/db/learning.db) accessed via crypto-learning-db MCP. Key queries:
get_portfolio_state()→ balances, open trades, statsquery_trades(symbol="BTC", status="open")→ filtered trade listget_trade_stats(symbol="BTC")→ aggregated win/loss statsrecord_trade(...)→ open a new trade (auto-deducts balance)close_trade(trade_id, exit_price, close_reason)→ close trade (auto-calculates PnL)
Trade fields include: id, symbol, side, portfolio_type, entry_price, usd_amount, leverage, stop_loss, take_profit, strategy_type, reasoning, key_assumptions (JSON), agent_signals (JSON), learning (JSON)
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.
- 12d ago First seen · 244 lines · 30 tokens per session scan A 30583062e297
portfolio-manager is an agent published in the GitHub repository hugoguerrap/crypto-claude-desk (33 stars, last pushed 19d ago), licensed MIT. It adds 30 tokens to every session and 3,228 once invoked, about $0.0002 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 2026-08-30.
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