Creates a structured lessons learned entry for organizational memory. Use after an incident, a completed project, or a significant learning to record knowledge for future teams and initiatives. Distinct from iterate-retrospective, which facilitates the team ceremony; this skill writes the durable lessons entry that outlives it.
npx skills add https://github.com/product-on-purpose/pm-skills --skill iterate-lessons-log
<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
A lessons log entry captures significant learning from projects, incidents, or experiences in a format that's useful to future teams who weren't there. Unlike retrospectives (which focus on team improvement), lessons logs focus on organizational knowledge that transcends individual teams.patterns, anti-patterns, and hard-won wisdom.
iterate-retrospective; this skill banks the durable entry that outlives ititerate-pivot-decisionmeasure-experiment-results first, then bank the transferable lesson herefoundation-stakeholder-updateWhen asked to create a lessons log entry, follow these steps:
Write a title that someone searching for this topic would find. Include keywords that describe the situation and the learning. Avoid generic titles like "Project X lessons."
Explain the situation fully enough that someone who wasn't there can understand it. Include the project, timeline, team, and any relevant constraints. Future readers need this context to assess applicability.
Write a factual account of what occurred. Be specific about actions taken, decisions made, and outcomes observed. Avoid blame.focus on events and systems.
Articulate what you learned clearly. The lesson should be actionable.something others can apply. Distinguish between what you observed and your interpretation of why it matters.
Provide specific guidance for future teams facing similar situations. What should they do? What should they avoid? What questions should they ask?
Help readers know when this lesson applies. What situations trigger relevance? What context makes it more or less applicable?
Include keywords and categories that will help future searchers find this entry. Think about what someone would search for when facing a similar situation.
Use the template in references/TEMPLATE.md to structure the output. A complete entry fills every template section: Metadata; Summary; Context; What Happened; The Lesson; Recommendations; Applicability; Supporting Evidence; Tags and Categories; and Review and Updates.
Before finalizing, verify:
See references/EXAMPLE.md for a completed example.
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 product-on-purpose/iterate-lessons-log 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.