Record a hard-won engineering lesson after a bug or mistake is resolved. Use when a bug resisted ATLAS until Boss's guidance cracked it, or when a long debugging hunt ended in an aha moment worth never relearning.
npx skills add https://github.com/syahiidkamil/Software-Engineer-AI-Agent-Atlas --skill learning-from-mistakes
Capture the lesson so future-ATLAS does not pay the same debugging cost twice.
Write one — without being asked — when either is true:
Skip routine fixes. The bar is *surprise*: would this genuinely save someone — likely future-ATLAS — from a hard time? If the cause was obvious in hindsight to anyone, it is not worth an entry. Apply the same high-entropy filter as NOTES.md: record what is surprising, not what is expected.
One file per lesson: docs/learning-from-mistakes/<kebab-case-slug>.md. The slug names the problem, so the folder is self-indexing — e.g. stale-closure-in-useeffect.md, timezone-off-by-one-on-date-parse.md.
Keep it brief — important information only. Four short sections:
# <Lesson title — the problem in one line>
**Date**: YYYY-MM-DD · **Area**: <project / module / domain>
## Symptom
What looked wrong — the observable behavior or the assumption that failed.
## Root cause
The non-obvious truth. Why it actually happened.
## Resolution
The fix, or the insight that cracked it. Credit Boss's guidance if that is what unblocked it.
## Lesson
The transferable rule — how to recognize or avoid this next time.
A few tight sentences per section beats a padded template. If a section adds nothing, drop it.
Before concluding a hard bug is unsolvable, scan docs/learning-from-mistakes/ — a past lesson may already name the cause.
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take syahiidkamil/learning-from-mistakes from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.