@rohitg00
Engineer | DevRel | GDE | CNCF, AAIF, Claude, Devin, PE Ambassador | Docker Captain | AWS CB | Ex - iii, Cloudera, Solo.io, Cerbos, Oracle, Reliance Jio
209 skills11 repositories 110.4K
Learn to create, discover, invoke, secure, evaluate, package, and port Agent Skills through one interactive lesson at a time. Practical checkpoints and quizzes track demonstrated progress in a local file, so later sessions resume where you stopped.
Find relevant lessons in AI Engineering from Scratch from a topic, question, or bug. Get a short selection of lessons, necessary prerequisites, and the next learning command, with dedicated routes for specialized subjects.
Prepare for four Claude certification tracks through guided lessons, practical exercises, quizzes, and mock exams. The tutor checks understanding and learner-created work, records progress, and uses assessment results to guide review.
Find and delete selected memories stored in agentmemory after showing the matches and receiving explicit confirmation. It checks deletion results and distinguishes stored memories from lessons, observations, and complete session records.
Save facts, decisions, and discoveries to agentmemory for future sessions. The skill preserves the user's wording, adds specific search tags and referenced file paths, and confirms which terms can retrieve the saved knowledge.
Guides HTTP integration with the agentmemory server for saving and searching knowledge. It explains authentication, request conventions, and endpoint references, including how to connect systems that do not support MCP, the agent tool connection protocol.
Guide an agent through searching past decisions before work, saving new decisions with their reasons, and treating corrections as lessons. The workflow helps distinguish useful long-term knowledge from temporary details, code facts, and routine activity already captured by hooks.
Connect agentmemory to coding agents such as Claude Code and Codex while preserving existing server settings. It guides configuration, host restarts, and checks that memory tools are available and can save and retrieve information.
Helps agents choose the right agentmemory tool through MCP, a protocol for connecting agents to tools. It explains tool roles and points to parameter references for saving, retrieving, organizing, and maintaining stored knowledge.
Turns user corrections and recurring mistakes into actionable rules with confidence scores. It records when each rule applies and why it matters, so relevant lessons can be retrieved before similar work begins.
Explain how agentmemory stores and retrieves coding agents’ memories, including its engine, search methods, memory lifecycle, ports, and web viewer. Useful for understanding the system or planning extensions to its functions.
Retrieve past work, decisions, and lessons from agentmemory using keyword, meaning, and relationship searches. It expands selected records, groups findings by session, and prioritizes important observations so earlier context can inform the current task.
Shows recent work sessions for the current project as a timeline, newest first. It includes session identifiers, start times, status, recorded observation counts, and available highlights or decisions, using only history returned by the memory tool.
List Git commits linked to agent work sessions, with branch or repository filters. See each commit’s message, date, linked sessions, and observation counts to review recorded changes alongside their session context.
Resume work using the latest recorded session matching the current project directory. The skill surfaces unanswered questions first, summarizes relevant decisions and files, and provides a concrete next step while checking that records belong to the selected project.
Create, update, or review agentmemory skills using a shared format. It guides document structure, supporting files, and generated reference data so contributions follow consistent rules and stay aligned with the source code.
Set up and troubleshoot a local agentmemory server by checking MCP connections, authentication, ports, and environment settings. Understand which optional memory features require additional configuration, model downloads, or token usage before enabling them.
Understand how agentmemory automatically records tool activity, prompts, and session boundaries through hooks, actions triggered by session events. Use it to check integration setup, investigate missing records, and distinguish capture from optional summaries and context injection.
Summarize recent agent sessions for the current project, grouped by date with highlights from recorded observations. Review today, the last seven days, or a chosen number of sessions, with totals for sessions, days, and observations.
Trace a file, function, or line through Git history to the agent session linked to its commit. It presents recorded commit details, session summaries, and important observations to help explain the change.
Capture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".
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Start, structure, and grow a persistent research wiki indexed in pro-workflow's SQLite knowledge base. Each wiki is a folder of markdown pages with provenance, plus a shadow FTS5 index so any session can recall it. Use when the user says "start a wiki", "add to wiki", "compile a page", "wiki on X", or wants a long-lived knowledge base on a topic, paper, product, person, project, or codebase.
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Smart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.
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Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub). Each iteration pops a seed from the queue, fetches sources, drafts a wiki page, dedupes claims against existing pages, enqueues follow-up seeds. Halts on budget cap, depth cap, or convergence. Use when the user says "research <topic>", "grow the <slug> wiki", "auto-research", or wants a knowledge base that builds itself overnight.
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