Datasheet

How to Use

When a user requests datasheet extraction:

1. Identify the input: User provides either:

   • Local PDF path: /path/to/datasheet.pdf
   • URL: https://example.com/datasheet.pdf

2. Validate input:

   • For local files: Verify the file exists and is accessible
   • For URLs: Confirm the URL is well-formed

3. Delegate to agent:

   • Use the Task tool to invoke the datasheet-agent subagent
   • Provide clear context about the datasheet source (path or URL)
   • Let the agent execute the full 6-step extraction workflow autonomously

   Example delegation:

   "I'm delegating this datasheet extraction to the datasheet-agent.
   Please process [URL/path], extract goal-oriented information focused on
   circuit design and microcontroller code development, and save the focused
   markdown output to the datasheets/ directory."
   

4. Present results: When the agent completes, show the user:

   • File location (e.g., datasheets/74HC595.md)
   • Component name and key characteristics
   • Brief summary of what was extracted
   • Any issues or notes from extraction (missing sections, ambiguities resolved, etc.)

Agent Responsibilities

The datasheet-agent autonomously handles:

• Step 1: Receive and validate input (PDF path or URL)
• Step 2: Read datasheet using Read tool (PDF) or WebFetch (URL)
• Step 3: Extract 2 goal-oriented sections focused on circuit design and code development
• Step 4: Generate focused markdown file (~90-120 lines) with proper formatting
• Step 5: Verify completeness, accuracy, and focused scope
• Step 6: Return summary with file location and key component info

For full workflow details, see .claude/agents/datasheet-agent.md

Example Invocations

User might say:

• "Extract this datasheet: https://www.ti.com/lit/ds/symlink/sn74hc595.pdf"
• "Summarize the ATmega328P datasheet for me"
• "I need documentation for this IC: /path/to/lm358.pdf"
• "Help me understand the 74HC595"
• "/datasheet https://example.com/datasheet.pdf"

Reference Materials

• Example output format: See references/example_output.md for a complete example of expected markdown output
• Agent workflow details: See ../../.claude/agents/datasheet-agent.md for complete extraction workflow

Benefits of Agent-Based Architecture

• Context efficiency: PDF content stays in agent's isolated context, not main conversation
• Clean conversation: Main conversation only sees high-level progress and final summary
• Token savings: ~9,000+ tokens saved in main conversation for typical datasheet (PDF content discarded when agent completes)
• Consistent output: Agent follows same workflow every time, ensuring reliable results
• Easy maintenance: Update agent definition without changing skill interface