nemo-rl-session-memory
Manage durable working-session memory for coding agents. Use when a user asks to preserve or recover agent context across disconnects, VS Code restarts, long-running work, handoffs, or any session where important state should be written periodically under the repo's session directory. Do NOT use for: simple questions, short tasks, one-off commands, linting, or code review.
What this skill does
# Session Memory Keep a durable, human-readable record of the current working session so another agent can resume after a disconnect with minimal context loss. ## When To Use Use this skill when: - The user asks to preserve, recover, checkpoint, or manage agent memory. - Work is long-running, experimental, or likely to span disconnects. - You are about to make nontrivial edits, run long jobs, switch branches, or pause for user input. - You resume in a repo that already has `./session/` directories. ## Session Directory Create one directory per working session: ```bash mkdir -p session date +%Y%m%d_%H%M%S mkdir -p session/<session_date_time> ``` Use local time from the machine. Reuse the same session directory for all checkpoints in the same conversation unless the user explicitly starts a new session. Expected files: - `session_state.md` - overall goal, current subtask, loaded skills, status, plan, assumptions, blockers, and next actions. - `timeline.md` - append-only log of major actions, commands, results, and decisions. - `files.md` - files inspected, files changed, and why they matter. - `handoff.md` - concise resume instructions for the next agent. Add other files only when useful, such as `experiments.tsv`, `review_notes.md`, or copied command logs. ## Start Or Resume At the start of a session: 1. Check for existing session directories: ```bash ls -dt session/* 2>/dev/null | head ``` 2. If the user is resuming work, read the latest relevant `session_state.md`, `timeline.md`, and `handoff.md`. 3. If no relevant session exists, create a new timestamped directory. 4. Write an initial `session_state.md` with the user's overall goal, current subtask, loaded skills, repo path, branch, and known constraints. Do not treat session notes as the only source of truth. Verify important claims against git state, files, and command output before acting. ## Checkpoint Rhythm Write a checkpoint: - After gathering enough context to form a plan. - Before and after meaningful code edits. - Before long-running commands, experiments, branch switches, or anything hard to reconstruct from chat. - When the user changes direction. - Before final response if the session has meaningful state worth resuming. - At least every 30 minutes during active long-running work. Prefer updating the same files rather than creating many small checkpoint files. Keep the record compact and scannable. ## File Templates ### `session_state.md` ```markdown # Session State - Session: <session_date_time> - Repo: <absolute repo path> - Branch: <branch name> - Started: <local timestamp> - Updated: <local timestamp> ## Goal <Stable overall user goal in one or two sentences. Preserve this across follow-up steering unless the user explicitly changes it.> ## Current Subtask <Immediate task or steering request currently being handled.> ## Loaded Skills - `<skill-name>` - <why it was loaded and any important instructions to preserve.> ## Current Status <What is true now. Include completed work and verification status.> ## Plan - [ ] <Next concrete step> - [ ] <Next concrete step> ## Assumptions - <Assumption and how to verify it if needed.> ## Blockers - <Blocker or "None known".> ``` ### `timeline.md` ```markdown # Timeline ## <local timestamp> - User asked: <brief request> - Context gathered: <files/commands and key result> - Decision: <important choice and rationale> - Result: <edits/tests/outcome> ``` ### `files.md` ```markdown # Files ## Inspected - `<path>` - <why it mattered> ## Changed - `<path>` - <what changed and why> ## Generated - `<path>` - <purpose> ``` ### `handoff.md` ```markdown # Handoff ## Resume From Here <One paragraph summary of the current state.> ## Next Actions - <Most important next action> - <Verification or cleanup still needed> ## Watch Outs - <Risks, user preferences, or repo constraints the next agent must preserve.> ``` ## Recovery Workflow When resuming after a disconnect: 1. Find the likely latest session directory. 2. Read `handoff.md` first, then `session_state.md`, then recent `timeline.md`. 3. Run lightweight verification such as `git status --short`, `git branch --show-current`, and targeted file reads. 4. Continue from the latest verified next action. 5. Append a timeline entry noting the recovery and any mismatches found. ## Quality Rules - Keep notes factual and terse. Future agents need state, not a transcript. - Record command outcomes that matter, especially failed tests or skipped verification. - Mention uncommitted changes and whether they were made by the current agent or pre-existing. - Do not store secrets, tokens, private credentials, or large logs in session files. - If a session file becomes large, summarize old details and keep the latest next actions near the top of `handoff.md`.
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.