raman-fitting
Raman Fitting
Overview
This skill guides the analysis and curve fitting of Raman spectroscopy data, particularly for materials like graphene where characteristic peaks (G, D, 2D bands) must be accurately extracted. The primary challenge in these tasks is ensuring correct data ingestion before any analysis begins.
Critical First Step: Data Parsing Verification
Before any fitting or analysis, verify data is parsed correctly. This is the most common source of failure in spectroscopic data analysis.
Data File Inspection Protocol
- Read raw file content first - Examine the first 5-10 lines of the raw data file to understand the actual format
- Identify potential format issues:
- Line number prefixes (e.g., "1→", "2→" before actual data)
- Decimal separators (comma vs period - European vs US format)
- Column delimiters (tab, comma, semicolon, whitespace)
- Header lines that need to be skipped
- Encoding issues (UTF-8, ISO-8859-1, etc.)
More from letta-ai/skills
extracting-pdf-text
Extract text from PDFs for LLM consumption. Use when processing PDFs for RAG, document analysis, or text extraction. Supports API services (Mistral OCR) and local tools (PyMuPDF, pdfplumber). Handles text-based PDFs, tables, and scanned documents with OCR.
257imessage
Send and read iMessages/SMS from macOS. Use for texting contacts, scheduling services, or automating message-based workflows. Triggers on queries about texting, messaging, SMS, iMessage, or contacting someone via text.
206video-processing
Guide for video analysis and frame-level event detection tasks using OpenCV and similar libraries. This skill should be used when detecting events in videos (jumps, movements, gestures), extracting frames, analyzing motion patterns, or implementing computer vision algorithms on video data. It provides verification strategies and helps avoid common pitfalls in video processing workflows.
189letta-api-client
Build applications with the Letta API — a model-agnostic, stateful API for building persistent agents with memory and long-term learning. Covers SDK patterns for Python and TypeScript. Includes 24 working code examples.
147google-workspace
Connect to Gmail and Google Calendar via OAuth 2.0. Use when users want to search/read emails, create drafts, search calendar events, check availability, or schedule meetings. Triggers on queries about email, inbox, calendar, schedule, or meetings.
127portfolio-optimization
Guidance for implementing high-performance portfolio optimization using Python C extensions. This skill applies when tasks require optimizing financial computations (matrix operations, covariance calculations, portfolio risk metrics) by implementing C extensions for Python. Use when performance speedup requirements exist (e.g., 1.2x or greater) and the task involves numerical computations on large datasets (thousands of assets).
101