Results for “flashback”

Retro

Runs a full retrospective and dev cycle analysis, chaining /recall and /new-features to reconstruct what went wrong, extract lessons learned, identify rework patterns, and synthesize feature ideas from the findings.

Mines git history and codebase to reconstruct the development lifecycle, identify sequential and parallel patterns, and produce actionable recommendations for future iterations.

Facilitate a structured sprint retrospective to surface insights and produce actionable improvements with owners and deadlines.

Weekly engineering retrospective. (gstack)

Builds a local RAG memory system that indexes session logs and notes into ChromaDB for semantic recall across agent restarts.

Analyzes repeated agent failures or noisy routing and proposes evidence-backed changes to instructions, skills, gates, or runbooks.

Restore working context saved earlier by /context-save. Loads the most recent saved state (across all branches by default) so you can pick up where you left off — even across Conductor workspace handoffs. Use when asked to "resume", "restore context", "where was I", or "pick up where I left off". Pair with /context-save. Formerly /checkpoint resume — renamed because Claude Code treats /checkpoint as a native rewind alias in current environments. (gstack)

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

Facilitates structured sprint retrospectives, analyzing team feedback and sprint data to generate prioritized, actionable improvement items.

Weekly engineering retrospective. (gstack)

Weekly engineering retrospective. (gstack)

Conduct a retrospective on a coding session.

Facilitate a structured sprint retrospective — what went well, what didn't, and prioritized action items with owners and deadlines. Use when running a retrospective, reflecting on a sprint, creating action items from team feedback, or learning how to run effective retros.

Restore working context saved earlier by /context-save. (gstack)

Recover context from local AI conversation history with RecallBase. Use for same-day work summaries, resuming prior AI or coding sessions, or tracing a past decision to its source.

Injects up to 1 million tokens of external context into AI agent memory, auto-summarizes conversations with tone and intent preservation, and compresses multi-turn history into dense token sequences.

Engineering retrospective — generates a data-driven report of development velocity, commit patterns, hotspots, and team insights from git history. Saves results for week-over-week comparison.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Autopsy a stuck project, extract salvageable artifacts, and route to a fresh start via $bootstrap-repo reset or new-repo bootstrap

Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).

Diagnose your own behavior by reading the structured logs you leave behind — turns.jsonl, events.jsonl, chat_history.jsonl, scheduler.yaml. Use when something has gone wrong (a message didn't land, a scheduled job isn't firing, a communication pattern feels off), when you need to understand a pattern over many turns, or when cost / token usage needs auditing. Covers jq query recipes and points at the debugging-jobs / debugging-communication / debugging-drift companion guides for specific failure modes.

Per-channel skip-existing checks in Snakemake wrapper scripts for resuming interrupted SLURM jobs. Trigger: Snakemake interrupted job, skip existing channels, resume incomplete cycle, sentinel missing but outputs exist, per-channel completeness check, wrapper script resume logic.

Multi-tiered memory management (HOT/WARM/COLD) for context compaction. Invoke ONLY for explicit compaction events: post-`/compact` cleanup, MEMORY.md tier promotion, archive batch, or "trim my context". NOT for general recall (use deep-recall) or routine memory writes (use storage-router). Triggers: "compact memory", "promote to durable", "archive old context", "tier this".

Post-epic review to extract lessons and assess success. Use when the user says "run a retrospective" or "lets retro the epic [epic]"

Semantic-search personal knowledge (memory, plans, handoffs, skills, Codex rules) via the local RAG index at ~/.claude/rag-index/. Use when a query is fuzzy or cross-file ("how did we fix X", "what did we decide about Y", "which skill handles Z"). Complements grep (exact) and Serena (code symbols). If the user asks a recall question that doesn't map to a specific known file, reach here first.

Regenerate the iOS debug bridge against the latest upstream gstack templates. (gstack)

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

罗子君（都市剧虚构）认知与表达框架（压缩蒸馏）：全职太太 reboot、成长线与争议依赖 触发：我的前半生 等。虚构

Tracks crypto and AI narratives with mindshare scores, velocity arrows, phase labels, named drivers, and position calls. Detects phase transitions and reflexivity signals.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

灶门祢豆子（少年漫）认知与表达框架（压缩蒸馏）：竹筒萌点、鬼化反差、兄妹羁绊 触发：鬼灭之刃 等。虚构

Creates a technical journey retrospective document from a coding session, capturing decisions, tradeoffs, and debugging moments in a developer blog post style.

セッション再開時に最新5件のhandoffを読み込み文脈を復元するスキル。「おはよう」「こんにちは」「こんばんは」「再開」「restart」または /resume-session を呼んだ時にトリガーする。new-session の対（読込側）。

小丸子（子供向）认知与表达框架（压缩蒸馏）：懒散可爱、家族群像、童年微小确幸 触发：樱桃小丸子 等。全年龄