sutro-sync
Use at the start of any session and before pushing. Syncs Telegram, Google Docs, and GitHub state for the Sutro Group research workspace.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Use at the start of any session and before pushing. Syncs Telegram, Google Docs, and GitHub state for the Sutro Group research workspace.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | sutro-sync |
| description | Use at the start of any session and before pushing. Syncs Telegram, Google Docs, and GitHub state for the Sutro Group research workspace. |
Run this at session start and before any push. Covers three sources: Telegram, Google Docs, GitHub.
bin/tg-sync
Syncs 6 forum topics to a local SQLite database (telegram.db). First run does a full backfill; subsequent runs are incremental (only new messages).
Query recent messages from priority topics to check for new questions, directions, or results:
sqlite3 telegram.db "SELECT date, sender, substr(text, 1, 150) FROM messages
WHERE topic_id IN (SELECT id FROM topics WHERE slug IN ('chat-yad', 'chat-yaroslav', 'challenge-1-sparse-parity'))
AND date > datetime('now', '-3 days')
ORDER BY date DESC LIMIT 15"
Report anything relevant to the user.
Fallback: If telegram.db doesn't exist and credentials aren't configured, read the committed JSON files in src/sparse_parity/telegram_sync/ instead (may be stale).
Prerequisites: bun install, .env with TELEGRAM_API_ID and TELEGRAM_API_HASH, tg auth login (one-time). Full setup: docs/tooling/telegram-setup.md.
python3 src/sync_google_docs.py
Pulls 15+ Google Docs to docs/google-docs/. After syncing:
docs/google-docs/sutro-group-main.md for new meeting doc linkspython3 src/sync_google_docs.py --add "URL" "name" "Description"
python3 src/sync_google_docs.py # re-run
!!! info admonition) to new docsmkdocs.yml nav under Meetings > Google Docsdocs/meetings/index.md and docs/meetings/notes.mdPrerequisites: pandoc (brew install pandoc). Docs must be "Anyone with the link" sharing.
gh pr list --repo cybertronai/SutroYaro --state open
gh issue list --repo cybertronai/SutroYaro --state open
Check for new PRs from contributors (Andy/zh4ngx, Michael, others). Review code, verify results are reproducible, check that DISCOVERIES.md is updated.
Check docs/index.md (homepage) for stale numbers and missing features:
import re
# Check experiment count matches DISCOVERIES.md
with open('DISCOVERIES.md') as f:
disc = f.read()
exp_count = len(re.findall(r'^\| exp_', disc, re.MULTILINE))
with open('docs/index.md') as f:
index = f.read()
# Flag if homepage says fewer experiments than DISCOVERIES.md has
if f'{exp_count}' not in index:
print(f'WARNING: homepage may be stale. DISCOVERIES.md has {exp_count} experiments.')
# Check challenge count
challenges = ['sparse-parity', 'sparse-sum', 'sparse-and']
for c in challenges:
if c not in index:
print(f'WARNING: homepage missing challenge: {c}')
Also check:
bin/ scripts?If anything is stale, update docs/index.md before pushing.
docs/changelog.md (bump version)python3 -m mkdocs build to verify no broken linksgit pushpython3 -m mkdocs gh-deploy --forceThis skill works with any AI coding tool that reads files:
.claude/skills/ automatically.cursorrulesdocs/tooling/sync-runbook.mdAll state lives in files (JSON, markdown, YAML). No tool-specific APIs needed.
Use periodically (weekly or before a release) to find stale numbers, outdated descriptions, broken links, and inconsistencies across the codebase. Run after merging multiple PRs or before preparing a meeting report.
Use before a Sutro Group meeting to compile results and prepare a presentation report.
Use when running a new experiment. Follows the two-phase protocol from LAB.md.
Use before any research task, experiment, or PR review. Loads current project state from DISCOVERIES.md, open questions, and recent Telegram discussion.
Use at the start of a weekly session. Syncs all sources and generates a catch-up summary.
Use when drafting, editing, or reviewing any prose to detect and remove AI writing patterns including overused vocabulary (delve, tapestry, landscape), formulaic structures (binary contrasts, rule of three), throat-clearing openers, business jargon, and other LLM tells