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Use when recalling what a past assistant knew, searching old conversations, rendering specific chats, seeding reference memory from export sidecars, or mining historical context without doing a full import.\nlicense: MIT\n---\n\n# Navigating Chat History Without Digesting Everything\n\nUse this skill when the goal is **referenceable history**, not immediate full ingestion.\n\n## Good fits\n\n- search my exported ChatGPT history for a topic\n- figure out what the old assistant knew about me\n- render the conversation where we discussed X\n- keep this export around as external memory and only mine it when needed\n- seed MemFS from `memories.json` or `projects.json`\n\n## Default posture\n\nTreat the export as an archive you can navigate later.\n\n1. read the MemFS archive index first if it exists: `reference\u002Fchatgpt\u002Findex.md`\n2. inspect the export with `scripts\u002Finspect-export.py`\n3. search or list before rendering broad ranges\n4. preserve findings to `reference\u002Fchatgpt\u002F` first\n5. promote to `system\u002Fhuman.md` only when the fact is durable, current, and worth carrying every turn\n\nDo **not** re-digest the entire archive unless the user explicitly wants that.\n\n## Archive layout in MemFS\n\nKeep the external-memory archive under `reference\u002Fchatgpt\u002F`.\n\nRecommended files:\n\n- `reference\u002Fchatgpt\u002Findex.md` — source exports, schema notes, known paths, retrieval strategy\n- `reference\u002Fchatgpt\u002Fexport-YYYY-MM-DD.md` — inventory and sidecar summary for one export\n- `reference\u002Fchatgpt\u002Fchatgpt-memory-summary-YYYY-MM-DD.md` — content from `memories.json`\n- `reference\u002Fchatgpt\u002Fprojects-YYYY-MM-DD.md` — projects sidecar summary when useful\n- `reference\u002Fchatgpt\u002Ftranscripts\u002FNNN-slug.md` — curated high-signal conversation summaries\n- `reference\u002Fchatgpt\u002Fnotes\u002F` — topic-specific notes mined later\n\nPrefer progressive memory. Keep active memory small.\n\n## Scripts\n\n### `scripts\u002Finspect-export.py`\n\nUse first. It inventories the export and reads sidecars such as `memories.json`, `projects.json`, and `users.json`.\n\n```bash\npython3 scripts\u002Finspect-export.py \u003Cexport-path>\npython3 scripts\u002Finspect-export.py \u003Cexport-path> --output \u002Ftmp\u002Fexport-summary.md\n```\n\n### `scripts\u002Flist-conversations.py`\n\nUse to browse by title, recency, or message count.\n\n```bash\npython3 scripts\u002Flist-conversations.py \u003Cexport-path> --limit 25\npython3 scripts\u002Flist-conversations.py \u003Cexport-path> --title-contains Letta --sort messages\n```\n\n### `scripts\u002Fsearch-conversations.py`\n\nUse when titles are not enough.\n\n```bash\npython3 scripts\u002Fsearch-conversations.py \u003Cexport-path> --query \"Recovery Bench\"\npython3 scripts\u002Fsearch-conversations.py \u003Cexport-path> --query TFCC --role user --limit 20\n```\n\n### `scripts\u002Frender-conversation.py`\n\nUse for one conversation once you know the index.\n\n```bash\npython3 scripts\u002Frender-conversation.py \u003Cexport-path> --index 212\npython3 scripts\u002Frender-conversation.py \u003Cexport-path> --index 212 --compact-nontext --output \u002Ftmp\u002Fchat-212.md\n```\n\n### `scripts\u002Frender-range.py`\n\nUse only for focused batches after search narrows the field.\n\n```bash\npython3 scripts\u002Frender-range.py \u003Cexport-path> --start-index 210 --end-index 220 --output-dir \u002Ftmp\u002Fchat-range\n```\n\n## Workflow\n\n### 1. Anchor yourself in existing MemFS notes\n\nBefore touching the raw export, check whether the archive already has:\n\n- an export summary\n- a prior project summary\n- curated transcripts\n- a note on the same topic\n\nIf yes, use that first.\n\n### 2. Inspect before mining\n\nRun `inspect-export.py` to answer:\n\n- what export shape is this?\n- how many conversations are there?\n- does `memories.json` already contain a synthesized memory block?\n- does `projects.json` hold useful background?\n\nFor large archives, this often answers the question before raw conversation mining is needed.\n\n### 3. Narrow, then render\n\nPrefer this sequence:\n\n1. `list-conversations.py` for browse\n2. `search-conversations.py` for content lookup\n3. `render-conversation.py` for deep read\n4. `render-range.py` only when several adjacent conversations matter\n\nDo not render dozens of chats just because you can.\n\n### 4. Write findings to progressive memory first\n\nWhen a conversation matters, summarize it into:\n\n- `reference\u002Fchatgpt\u002Ftranscripts\u002F` for high-signal conversation summaries\n- `reference\u002Fchatgpt\u002Fnotes\u002F` for topic notes\n\nOnly then decide whether anything belongs in `system\u002Fhuman.md`.\n\n### 5. Promotion rule\n\nPromote to active memory only when the fact is:\n\n- explicit or strongly evidenced\n- current rather than historical-only\n- likely useful across many future conversations\n- low-risk to keep in context every turn\n\nEverything else can stay in `reference\u002Fchatgpt\u002F`.\n\n## Reference files\n\nRead `references\u002Frepository-layout.md` when creating or extending the MemFS archive layout.\n\n## Notes on export formats\n\nThis skill is designed for newer exports that contain `conversations.json` with `chat_messages`, while still handling older shard-based exports with `conversations-*.json` and `mapping` graphs.\n\nWhen in doubt, start with `inspect-export.py` instead of assuming the 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Use only when the user asks to change current Desktop\u002FLCD settings such as theme, default working directory, remote access preference, or remote environment name via the preferences JSON.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1303,1306,1309],{"name":1304,"slug":1305,"type":16},"Configuration","configuration",{"name":1307,"slug":1308,"type":16},"Desktop","desktop",{"name":1310,"slug":1311,"type":16},"Themes","themes","2026-07-13T06:23:41.407811",{"slug":1314,"name":1314,"fn":1315,"description":1316,"org":1317,"tags":1318,"stars":1206,"repoUrl":1207,"updatedAt":1323},"finding-agents","locate and manage agents on server","Find other agents on the same server. Use when the user asks about other agents, wants to migrate memory from another agent, or needs to find an agent by name or tags.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1319,1320],{"name":1198,"slug":1199,"type":16},{"name":1321,"slug":1322,"type":16},"Management","management","2026-07-16T06:02:17.297841",{"slug":1325,"name":1325,"fn":1326,"description":1327,"org":1328,"tags":1329,"stars":1206,"repoUrl":1207,"updatedAt":1335},"generating-mod-envs","generate Letta mod learning environments","Generates and reviews mod learning env JSON files for Letta Code local mods. Use when asked to teach, learn, or optimize a mod behavior; create, draft, validate, improve, or explain envs for `\u002Fmods learn --env`; or design evaluation scenarios, memory fixtures, requiredResultMarkers, requiredTraceMarkers, negative controls, and candidate diversity hints.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1330,1331,1334],{"name":1198,"slug":1199,"type":16},{"name":1332,"slug":1333,"type":16},"AI Infrastructure","ai-infrastructure",{"name":1304,"slug":1305,"type":16},"2026-07-13T06:23:08.838181",{"slug":1337,"name":1337,"fn":1338,"description":1339,"org":1340,"tags":1341,"stars":1206,"repoUrl":1207,"updatedAt":1350},"image-generation","generate images from text prompts","Generate images from text prompts (and optionally edit\u002Fremix input images). Use when the user asks to create, generate, draw, render, or edit an image, illustration, logo, icon, diagram, or photo.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1342,1345,1348],{"name":1343,"slug":1344,"type":16},"Creative","creative",{"name":1346,"slug":1347,"type":16},"Graphics","graphics",{"name":1349,"slug":1337,"type":16},"Image Generation","2026-07-13T06:23:06.189403",69,{"items":1353,"total":1465},[1354,1368,1383,1402,1415,1436,1446],{"slug":1355,"name":1355,"fn":1356,"description":1357,"org":1358,"tags":1359,"stars":23,"repoUrl":24,"updatedAt":1367},"1password","manage secrets with 1Password CLI","Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading\u002Finjecting\u002Frunning secrets via op.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1360,1363,1364],{"name":1361,"slug":1362,"type":16},"Authentication","authentication",{"name":1271,"slug":1272,"type":16},{"name":1365,"slug":1366,"type":16},"Security","security","2026-07-13T06:24:39.504387",{"slug":1369,"name":1369,"fn":1370,"description":1371,"org":1372,"tags":1373,"stars":23,"repoUrl":24,"updatedAt":1382},"agent-slack","automate Slack messaging and workflows","Slack automation CLI — read\u002Fsend\u002Fsearch messages, browse threads and channels, manage channels, download attachments, look up users, and run workflows.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1374,1375,1376,1379],{"name":1201,"slug":1202,"type":16},{"name":1271,"slug":1272,"type":16},{"name":1377,"slug":1378,"type":16},"Messaging","messaging",{"name":1380,"slug":1381,"type":16},"Slack","slack","2026-07-13T06:23:51.908511",{"slug":1384,"name":1384,"fn":1385,"description":1386,"org":1387,"tags":1388,"stars":23,"repoUrl":24,"updatedAt":1401},"ai-news","fetch and summarize AI news","Fetch and summarize recent AI news from curated RSS feeds (Hugging Face, VentureBeat, The Verge, OpenAI, Anthropic, DeepMind, etc.) and YouTube channels (Yannic Kilcher, Two Minute Papers, AI Explained, etc.). Also fetches full transcripts for specific YouTube videos. Use when the user asks about recent AI news, what's happened in AI lately, summaries of AI research or product announcements, or wants a digest of what's going on in the AI space.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1389,1392,1395,1398],{"name":1390,"slug":1391,"type":16},"Communications","communications",{"name":1393,"slug":1394,"type":16},"LLM","llm",{"name":1396,"slug":1397,"type":16},"Research","research",{"name":1399,"slug":1400,"type":16},"Summarization","summarization","2026-07-13T06:24:20.520223",{"slug":1403,"name":1403,"fn":1404,"description":1405,"org":1406,"tags":1407,"stars":23,"repoUrl":24,"updatedAt":1414},"creating-letta-code-channels","build and debug Letta Code channels","Builds and debugs Letta Code channels, including first-party channel adapters and dynamic user channel plugins under ~\u002F.letta\u002Fchannels. Use when adding Telegram, WhatsApp, Bluesky, Slack, Discord, or custom channel support; testing channel routing, pairing, MessageChannel, runtime dependencies, or channel plugin manifests.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1408,1409,1412,1413],{"name":1198,"slug":1199,"type":16},{"name":1410,"slug":1411,"type":16},"API Development","api-development",{"name":1377,"slug":1378,"type":16},{"name":1380,"slug":1381,"type":16},"2026-07-13T06:25:55.843495",{"slug":1416,"name":1416,"fn":1417,"description":1418,"org":1419,"tags":1420,"stars":23,"repoUrl":24,"updatedAt":1435},"datadog","query Datadog observability data","Query Datadog observability data (logs, metrics, monitors, dashboards, hosts) via direct API. Use when investigating production issues, checking monitors, searching logs, or accessing Datadog data.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1421,1423,1426,1429,1432],{"name":1422,"slug":1416,"type":16},"Datadog",{"name":1424,"slug":1425,"type":16},"Logs","logs",{"name":1427,"slug":1428,"type":16},"Metrics","metrics",{"name":1430,"slug":1431,"type":16},"Monitoring","monitoring",{"name":1433,"slug":1434,"type":16},"Observability","observability","2026-07-13T06:24:27.990605",{"slug":1437,"name":1437,"fn":1438,"description":1439,"org":1440,"tags":1441,"stars":23,"repoUrl":24,"updatedAt":1445},"discord","automate Discord server and channel tasks","Discord automation CLI — send\u002Fread\u002Fsearch messages, manage channels and servers, react, create threads, pin messages, and look up users.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1442,1443,1444],{"name":1201,"slug":1202,"type":16},{"name":1271,"slug":1272,"type":16},{"name":1377,"slug":1378,"type":16},"2026-07-13T06:24:26.62387",{"slug":1447,"name":1447,"fn":1448,"description":1449,"org":1450,"tags":1451,"stars":23,"repoUrl":24,"updatedAt":1464},"doc","create and edit Word documents","Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts\u002Frender_docx.py` for visual checks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1452,1455,1458,1461],{"name":1453,"slug":1454,"type":16},"Documents","documents",{"name":1456,"slug":1457,"type":16},"DOCX","docx",{"name":1459,"slug":1460,"type":16},"Office","office",{"name":1462,"slug":1463,"type":16},"Word","word","2026-07-13T06:23:44.299568",45]