briefing

# Briefing Command Triggers the Chief of Staff to generate an executive summary. ## Usage ```bash /briefing [period] # Example: /briefing today # Example: /briefing week /briefing --tokens [--since 7d|24h|30m] # Reports real session token usage from Claude Code JSONL. ``` ## Protocol 1. **Collect**: Gather logs from `kb/learnings/`, `maintenance/` logs, and recent runs. 2. **Synthesize**: Group by category (Ops, Strategy, Actions). 3. **Filter**: Remove low-priority success logs. 4. **Present**: Render the Daily Brief. ## Example ``` ## Daily Brief — 2026-04-23 ### Ops - night-watch: 3 dep updates shipped, 1 rolled back (breaking change in `x-pkg@2.0`) - health: all green except `mailpit` (degraded, non-critical) ### Strategy - predict: new PR #42 overlaps with in-flight refactor in `/src/auth` ### Actions needed - Review rollback from night-watch (ETA: 5 min) - Decide on `x-pkg` pin strategy (open question on GitHub #41) ``` ## Rules - **MUST** stay under 200 words unless the user explicitly asks for more detail - **MUST** lead with decision-relevant facts, not chronology — "what should I act on" before "what happened" - **NEVER** invent agent activity — report only what the logs show; absence of logs means "no data", not "nothing happened" - **CRITICAL**: separate Ops (what ran) from Strategy (what was decided) from Actions (what needs a human) — mixing them defeats the brief - **MANDATORY**: when no material activity exists for a category, omit the category heading instead of writing "none" ## Gotchas - `kb/learnings/` often mixes drafts with completed entries. Filter by frontmatter `status: final` or by filename convention before aggregating. - `maintenance/` branch logs from `/night-watch` use a different format (Shift Report markdown) than agent run logs. Do not concatenate blindly — parse each source separately and normalize. - "Recent runs" without an explicit time bound defaults to **everything** on some log backends. Always pass `--since` or a date filter, or you will read a week into yesterday's memory. - Successful runs outnumber interesting runs by an order of magnitude. Aggressively filter green/noop entries — they are the signal's noise floor. ## Token Receipts The `--tokens` flag reports real token usage parsed from Claude Code session JSONL — not estimates. Useful for: - Verifying `output-mode: concise` actually reduces tokens vs default sessions - Spotting expensive runs before they show up on the bill - Capturing a baseline before changing prompts or skills Underlying script: `scripts/session_token_stats.py`. ```bash # Aggregate current session python3 scripts/session_token_stats.py --json # Statusline-friendly one-line output python3 scripts/session_token_stats.py --statusline # Trend vs baseline python3 scripts/session_token_stats.py --statusline --baseline ~/.softspark/ai-toolkit/baseline.json ``` ### Status line (installed by default in v3.2.0+) `ai-toolkit install` wires `~/.claude/settings.json` to `app/hooks/ai-toolkit-statusline.sh`. The hook reads native Claude Code statusLine stdin (no session JSONL parsing) and renders one line: ``` ➜ <dir> git:(branch) ✗ ████░░░░░░ 43% ↑6.5k ↓252k effort:xhigh <model> ``` Segments left to right: - `➜ <dir>` — current directory basename - `git:(branch) ✗` — git branch + dirty marker - 10-cell **progress bar** for context-window usage. Color tiers: green `<70%`, orange `70–89%`, red `≥90%` - `↑in ↓out` — token arrows. Green up = input (upload), red down = output (download). Both cumulative across the session. - `effort:level` — Claude Code effort level (low / medium / high / xhigh) - model name Custom statusLine entries you set yourself (without the `_source: ai-toolkit` tag) are preserved untouched on install. Opt-outs (no reinstall required): - `AI_TOOLKIT_STATUSLINE_DISABLE=1` — silence the line entirely - `AI_TOOLKIT_STATUSLINE_NO_TOKENS=1` — hide token arrows segment - `AI_TOOLKIT_STATUSLINE_NO_GIT=1` — hide git segment - `AI_TOOLKIT_STATUSLINE_NO_EFFORT=1` — hide effort level segment - `AI_TOOLKIT_STATUSLINE_NO_COLOR=1` — disable ANSI colors - `AI_TOOLKIT_STATUSLINE_SHOW_COST=1` — append Claude Code's reported cost (`cost.total_cost_usd`) - `AI_TOOLKIT_STATUSLINE_DUMP=1` — write received stdin to `/tmp/cc-statusline-input.json` (debug) ### Save a baseline ```bash python3 scripts/session_token_stats.py --json | jq '.totals' > ~/.softspark/ai-toolkit/baseline.json export AI_TOOLKIT_STATUSLINE_BASELINE=~/.softspark/ai-toolkit/baseline.json ``` The statusline then renders trend arrows (↑ / ↓) against that baseline. ## When NOT to Use - For a specific production incident — use `/workflow incident-response` - For one-agent activity detail — read that agent's logs directly (`kb/learnings/<agent>/`) - For planning future work — use `/plan` or `/prd-to-plan` - For a technical system-up/down status — use `/health` - When no agents have produced logs in the window — say so and stop; do not pad