Institutional Flow Tracker

PassAudited by ClawScan on May 1, 2026.

Overview

This appears to be a coherent 13F analysis skill with disclosed FMP API-key use and user-directed setup, but users should treat its investment signals as research rather than automatic trading advice.

Before installing, be prepared to supply an FMP API key and install the requests dependency yourself. Run the scripts in a controlled Python environment, protect your API key, and treat the skill's buy/sell signals as research guidance rather than automatic financial advice.

Findings (3)

Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.

What this means

Running the scripts may consume the user's FMP API quota and exposes the FMP key to the script and FMP service.

Why it was flagged

The skill requires a third-party Financial Modeling Prep API key. This is expected for the stated 13F data-analysis purpose, but users should recognize that a credential is involved.

Skill content
Required: FMP API Key ... export FMP_API_KEY=your_key_here ... python3 scripts/track_institutional_flow.py --api-key YOUR_KEY
Recommendation

Use a dedicated FMP API key, prefer the environment variable over command-line arguments, and avoid pasting the key into shared chats, logs, or shell history.

What this means

Installing Python packages from the public package index can affect the local Python environment.

Why it was flagged

The skill relies on a user-installed Python dependency that is not pinned in an install spec. This is a common, purpose-aligned setup step, but it is still a supply-chain detail users should notice.

Skill content
No installation required beyond Python 3 and the `requests` library:

pip install requests
Recommendation

Install dependencies in a virtual environment and use trusted package sources; consider pinning a known-good requests version for repeatable use.

What this means

Users may over-trust the generated buy/sell labels or historical success-rate framing when making investment decisions.

Why it was flagged

The reference material includes strong investment-action language and performance-style claims. This is aligned with the skill's investment-analysis purpose, but it can influence high-stakes financial decisions.

Skill content
Action: BUY with conviction (2-5% portfolio position) ... Historical Success Rate: ~75-80% positive returns over 12 months
Recommendation

Use the output as one research signal, verify the underlying filings and assumptions, and do not treat the skill as personalized financial advice.