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CB portfolio-manager

Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.

tradermonty/claude-trading-skills Agent Skills author: tradermonty 21 files · 7 scripts body ≈ 6 550 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual…

As a process B 68/100 · Nearly there — weak spots: running it twice, progress reporting

IntegrationData and analyticsAI and agentsFinancetype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
82
Quality 40%
84
Run on models
none yet
Process rating
B
68/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 6

✓ No critical or high findings

Medium and low: 6
  • medium Dangerous commands cmd-shell-rc references/alpaca-mcp-setup.md:76
    Writes to a shell startup file
    echo 'export ALPACA_API_KEY="your_api_key_id"' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc references/alpaca-mcp-setup.md:77
    Writes to a shell startup file
    echo 'export ALPACA_SECRET_KEY="your_secret_key"' >> ~/.bashrc
  • medium Dangerous commands cmd-shell-rc references/alpaca-mcp-setup.md:78
    Writes to a shell startup file
    echo 'export ALPACA_PAPER=true' >> ~/.bashrc
  • low Dangerous commands cmd-shell-rc scripts/check_alpaca_connection.py:43
    Writes to a shell startup file (string literal in code, not executed)
    print("  echo 'export ALPACA_API_KEY=\"your_key\"' >> ~/.bashrc")
    code literal
  • low Dangerous commands cmd-shell-rc scripts/check_alpaca_connection.py:44
    Writes to a shell startup file (string literal in code, not executed)
    print("  echo 'export ALPACA_SECRET_KEY=\"your_secret\"' >> ~/.bashrc")
    code literal
  • low Dangerous commands cmd-shell-rc scripts/check_alpaca_connection.py:45
    Writes to a shell startup file (string literal in code, not executed)
    print("  echo 'export ALPACA_PAPER=\"true\"' >> ~/.bashrc")
    code literal

Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6550 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 68/100

  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Steps. 224 steps, 4 vague phrases
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6550 tokens
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • low 11 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 390: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 224 items
  • +3Output format is stated explicitly
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (10 of 10)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.