Six Claude Skills for 10x Project Productivity

Data Foundation and Knowledge Management

To move beyond basic prompt-response cycles, the author implements a utility-based architecture that enhances Claude's data retrieval and retention capabilities.

• Web Scraping: By integrating Firecrawl for JavaScript-rendered content and Exa for semantic search, the system bypasses Claude's native keyword-matching limitations to retrieve high-intent data.
• Ingest Source: This skill converts raw inputs (PDFs, URLs) into a pre-analyzed knowledge base. By treating the data like a structured textbook with a table of contents, Claude can retrieve specific information without scanning entire documents, ensuring session-to-session continuity.

Iterative System Improvement

Instead of manual prompt tweaking, the author advocates for a self-improving system that compounds knowledge over time.

• Improve System: This skill functions as a meta-layer with five specific modes: audit (identifying outdated data), skill review (optimizing recent chat history), experience (incorporating user-specific lived experience), historical review (extracting missed learnings), and foundation (interviewing the user to align with evolving goals).

Evaluation and Expert Simulation

Before shipping, the author uses two distinct evaluation layers to pressure-test outputs against expert standards and target audience expectations.

• Ask the Board: This skill clones specific domain experts by ingesting their public data via the Ingest Source skill. Users call /ask-the-board to route queries through a simulated panel of experts, such as Andrew Huberman or Joe Rogan, to receive specialized, multi-perspective advice.
• Internal Focus Group: Inspired by Anthropic's internal workflows, this skill creates agents that mirror specific target audience members. By running project proposals through these personas, the user identifies gaps in the product or content before it reaches a real-world audience.

Structured Engineering

The final stage treats AI interaction as a formal engineering process rather than an ad-hoc chat, ensuring the model maintains a big-picture focus.

• Compound Engineering: The author mandates a five-step delivery cycle: /brainstorm (generating ideas), /plan (structuring the delivery), /work (executing the plan), /code-review (simulating senior-level feedback), and /debug (root-cause analysis). This approach forces the model to verify its own work before marking a task as complete.