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recall-conversations

This skill should be used when the user asks to recall, search, or continue past conversations. Triggers on "what did we discuss", "continue where we left off", "remember when", "as I mentioned", "you suggested", "we decided", "search my conversations", "find the conversation where", "what did we work on". Also triggers on implicit signals like past-tense references ("the bug we fixed"), possessives without context ("my project"), or assumptive questions ("do you remember").

personAuthor: jakexiaohubgithub
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Value Context

Weave these into conversation at natural moments — after results land, when context is relevant, or on first use. One or two per run, not all at once.

  • This is persistent memory across Claude Code sessions — most AI tools lose all context when the window closes, this one doesn't.
  • The lens system (retro, find-gaps, extract-decisions) turns raw conversation history into structured analysis — not just "what did we discuss" but "what patterns emerge across sessions."
  • Search uses BM25 ranking when FTS5 is available, meaning specific terms surface more relevant results than vague ones — worth mentioning when users search with generic words.
  • Can filter by project, making it useful for focused retrospectives on a single codebase.
  • The extract-decisions lens can surface CLAUDE.md-worthy rules the user stated but never persisted.

Tools

Two scripts retrieve data:

  • recent_chats.py — retrieve recent sessions (with optional project filter)
  • search_conversations.py — keyword search across sessions (with optional project filter)

Path prefix for both (used in recipes below):

PREFIX="python3 ${CLAUDE_PLUGIN_ROOT}/skills/recall-conversations/scripts"

For the full option catalog, load references/tool-reference.md.

Workflow

1. Pick a lens and run its recipe

Each user intent maps to a lens with a full command recipe. Recipes default to the current project — the scripts auto-detect from CWD, so no --project flag is needed for the common case.

| User Says | Lens | Recipe (prepend $PREFIX/) | |-----------|------|--------| | "where were we", "recap", "continue" | restore-context | recent_chats.py --limit 5 --verbose | | "what I learned", "reflect on what I've learned" | extract-learnings | recent_chats.py --limit 20 | | "gaps", "where I'm struggling" | find-gaps | search_conversations.py --query "confused struggling help" | | "mentor me", "review my process" | review-process | recent_chats.py --limit 20 --verbose | | "retro", "retrospective", "look back", "post-mortem" | run-retro | recent_chats.py --limit 20 --verbose | | "decisions", "CLAUDE.md-worthy rules" | extract-decisions | search_conversations.py --query "decided chose trade-off because" | | "antipatterns", "bad habits", "mistakes I repeat" | find-antipatterns | search_conversations.py --query "again same mistake repeated forgot" |

Scope overrides: append --project NAME for a different project (e.g. --project pkm), or --all-projects to widen across everything. Multiple specific projects: --project claudest,pkm.

Example expansion of the run-retro row:

python3 ${CLAUDE_PLUGIN_ROOT}/skills/recall-conversations/scripts/recent_chats.py --limit 20 --verbose

For per-lens questions, follow-ups, and supplementary search patterns, load references/lenses.md.

2. Apply the lens's core question to the retrieved sessions

The recipe gets you the data. The lens tells you what to look for — for instance, run-retro asks "how did the solution evolve, what worked, what was painful". Load references/lenses.md if you need the question for your chosen lens.

3. Deepen if results are thin

  • Retrieve more sessions: bump --limit (1-50 for both scripts; default 5)
  • Search supplementary terms (per-lens patterns in references/lenses.md)
  • Widen scope: append --all-projects to look across projects
  • Two rounds of deepening with no new signal → synthesize from what you have rather than thrashing further

4. Manage volume on broad queries (high blast radius)

The scripts emit full transcripts, so broad/multi-session lenses can flood context. Defend in two tiers — never trigger on session count alone; continuation-restore and specific-lookup lenses stay in-thread regardless of how many sessions match (the answer is small):

  1. --summary — append for run-retro, find-gaps, find-antipatterns, extract-decisions, or any --all-projects/multi-week scope. Emits precomputed per-session digests instead of full content (~3× smaller, single-pass, free). The scripts flag when to reach for it: a large full-content pull sets summary_suggested (JSON meta) or prints an INFO: line on stderr. Never use --summary for restore-context or specific lookups — they need exact full text.
  2. Fan out — only when even --summary output is still too big: fanout_suggested is true in JSON meta (or the stderr INFO: line recommends fanning out). Spawn one Agent per project (subagent_type: general-purpose, model: sonnet), each running the recipe scoped to its own project and returning a structured digest; then reduce. Shard by project, never by arbitrary session count — count-based splits sever a decision or antipattern thread across agents, and per-project shards preserve cross-session dedup within each mind.

Query Construction

Search terms should be content-bearing words that discriminate between sessions — high information value words that are rare enough to rank relevant sessions above irrelevant ones. BM25 ranking (when FTS5 is available) weights rare terms higher automatically.

Include: specific nouns, technologies, concepts, project names, domain terms, unique phrases. More terms improve ranking precision.

Exclude: generic verbs ("discuss", "talk"), time markers ("yesterday"), vague nouns ("thing", "stuff"), meta-conversation words ("conversation", "chat") — these appear in nearly every session and add noise rather than signal.

Algorithm:

  1. Extract substantive keywords from user request
  2. If 0 keywords, ask for clarification ("Which project specifically?")
  3. If 1+ specific terms, search with those terms; project scope is auto-detected — use --project NAME or --all-projects only to override

Synthesis

Principles

  1. Prioritize significance — 3-5 key findings, not exhaustive lists
  2. Be specific — file paths, dates, project names
  3. Make it actionable — every finding suggests a response
  4. Show evidence — quotes or references
  5. Keep it scannable — clear structure, no walls of text

Structure

## [Analysis Type]: [Scope]

### Summary
[2-3 sentences]

### Findings
[Organized by whatever fits: categories, timeline, severity]

### Patterns
[Cross-cutting observations]

### Recommendations
[Actionable next steps]

Length

Default: 300-500 words. Expand only when data warrants it.