nntrivi2001
57dc91585d
Internal SmartGift build of a Claude Code monitoring dashboard. Lanes: a durable unit of parallel agent work, one per working directory, tracked across session restarts. Managed lanes are git worktrees the dashboard provisions and can reset or remove behind a three-check destroy guard and a counted preflight; adopted lanes are directories you already own and are never destroyable. Pipelines: a lane moves through pipeline stages. A stage the agent declares with evidence renders green; a stage inferred from the tool-event stream renders dashed amber and never counts as done. Detection is forward-only within a 30-minute window, and never writes the declared stage. Workspace: one page at /run with a lane grid, the selected lane's pipeline, and a full Claude console behind a disclosure.
62 lines
3.5 KiB
Markdown
62 lines
3.5 KiB
Markdown
---
|
||
description: >
|
||
Forecast Claude Code spend to the end of the week or month from the daily
|
||
session trend on the Agent Monitor dashboard — moving average of daily spend
|
||
× days remaining, added to spend-to-date. Uses /api/analytics daily_sessions,
|
||
/api/pricing/cost, and /api/sessions for a per-day cost curve.
|
||
Use when projecting cost or asking "where will my spend land".
|
||
---
|
||
|
||
# Spend Forecast
|
||
|
||
Project where Claude Code spend will end up by the close of the current week or month.
|
||
|
||
## Input
|
||
|
||
The user provides: **$ARGUMENTS**
|
||
|
||
This is the forecast horizon — `"week"`, `"month"`, or a specific date. Default to
|
||
**month** (calendar month-end) when nothing is given, and state the horizon you used.
|
||
|
||
## Data Sources
|
||
|
||
| Endpoint | Returns |
|
||
|----------|---------|
|
||
| `GET /api/analytics` | `{ total_cost, tokens (effective totals, baselines pre-summed), daily_sessions (365d: [{ date, count }]), daily_events, overview, ... }` — `daily_sessions` is the trend the forecast extrapolates |
|
||
| `GET /api/pricing/cost` | `{ total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] }` — authoritative spend-to-date and avg cost-per-session input |
|
||
| `GET /api/sessions?limit=200` | Session list with inline `cost` and `started_at` — group by day for a sharper daily-spend curve than the count-based approximation |
|
||
|
||
## Forecast method
|
||
|
||
Spend has no native per-day field, so build a daily-spend series and extrapolate:
|
||
|
||
1. **Spend-to-date** = `total_cost` from `/api/pricing/cost`.
|
||
2. **Avg cost per session** = `total_cost / total_session_count`.
|
||
3. **Daily spend series**: for the trailing window, `daily_spend[d] ≈ daily_sessions[d].count × avg_cost_per_session`. For a sharper curve, instead sum inline session `cost` grouped by `DATE(started_at)`.
|
||
4. **Moving average**: `avg_daily_spend = mean(daily_spend over the trailing 7 days)`. Also compute a 14-day average to gauge whether the trend is accelerating (▲) or cooling (▼).
|
||
5. **Remaining days**: days left until the end of the chosen horizon (week = through Sunday; month = through the last calendar day).
|
||
6. **Projection**: `projected_total = spend_to_date_this_period + (avg_daily_spend × days_remaining)`.
|
||
|
||
> Spend-to-date this period: when the trend covers more than the current period, restrict the spend-to-date term to sessions whose `started_at` falls inside the current week/month so the projection isn't inflated by older spend.
|
||
|
||
## Report Sections
|
||
|
||
### 1. Spend to date
|
||
`total_cost`, session count, avg cost/session, and how much falls inside the current period.
|
||
|
||
### 2. Daily trend
|
||
The 7-day and 14-day moving averages of daily spend, with a ▲/▼ accelerating-vs-cooling read. Show the last 7 days as a compact table (date, sessions, est. spend).
|
||
|
||
### 3. Projection
|
||
`avg_daily_spend × days_remaining` and the resulting `projected_total` for the horizon. State the days-remaining count explicitly.
|
||
|
||
### 4. Budget check (if a budget is known)
|
||
If the user mentions a budget, show projected vs. budget, the over/under delta, and the date the budget is projected to be crossed (`days_to_budget = (budget − spend_to_date) / avg_daily_spend`).
|
||
|
||
### 5. Confidence & caveats
|
||
Note that the forecast assumes the recent daily pace holds, that daily spend is approximated from session counts unless an inline-cost curve was used, and call out any low-data horizons (e.g. fewer than 7 active days).
|
||
|
||
## Output
|
||
|
||
Markdown with the trend table and the projection. Currency as USD to 4 decimal places; show moving averages and the projected total prominently. Deltas with ▲/▼.
|