Estimate future spending from recent usage costs, with projections for 7, 30, 90, and 365 days. When a budget is configured, see how many days remain before spending reaches key budget thresholds.
Forward-looking spend extrapolation. Computes a USD-per-day rate from the recent measurement window, projects to 7d/30d/90d/365d horizons, and surfaces "days until budget exhausted" when a budget is configured. Predictive counterpart to `cost-budget-check` (reactive).
Review the instructions the agent will receive before you install.
Forward-looking cost projection that pairs with cost-budget-check:
cost-budget-check answers "have we crossed the line?" — reactivecost-projection answers "when will we cross the line?" — predictivesession-* records from the cost-tracking namespace (same source cost-budget-check uses).capturedAt/startedAt).windowSpend / windowDays.budget-config key set by cost-budget set):
ALREADY REACHED markers for thresholds already exceeded.--window <duration> Measurement window. Nh|Nd|Nw|Nm. Default 7d.
--horizons <csv> Projection horizons. Default 7d,30d,90d,365d.
--format table|json Default table (markdown).
Env: PROJECTION_NAMESPACE override (default cost-tracking), PROJECTION_QUIET=1 (alias for --format json).
| Sessions in window | 3 |
| Window spend | $3.000000 |
| **USD per day** | **$0.428571** |
| All-time spend | $3.000000 across 3 sessions |
## Projected spend (linear extrapolation)
| Horizon | Days | Projected spend |
|---|---:|---:|
| 7d | 7 | $3.0000 |
| 30d | 30 | $12.8571 |
## Budget exhaustion ($20.00 configured)
| Threshold | Target | Remaining | Time at current rate |
|---|---:|---:|---|
| 75% | $15.00 | $12.00 | 28.0 days |
| 90% | $18.00 | $15.00 | 35.0 days |
| 100% | $20.00 | $17.00 | 39.7 days |
cost-projection --format json | jq '.budget.exhaustion[2].daysUntilReached < 7' → fail builds when 100% exhaustion is < 1 week away.Linear extrapolation assumes the current rate holds. The footer reminds operators to re-run after workload shifts. For drift detection over MULTIPLE windows, pair with cost-trend (which already covers benchmark-drift).
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Compare models available through the HuggingFace router with chat-ui configuration, research missing models, and write short English descriptions of their architecture and capabilities. Add entries to both production and development configuration files and commit the changes.
Create an Architecture Decision Record, a document for recording important design choices, with the next sequential number. It generates a Markdown template, registers the record in AgentDB, and links related decisions found through search.
Build a searchable index and relationship graph from ADRs, records of architectural decisions. Import two supported document formats, refresh existing metadata without duplicate relationships, and review summaries of statuses, missing references, and inconsistencies.
Rebuild the index of ADRs, records of architectural decisions, after files or relationship lines are deleted. It clears stored records and relationships, indexes the files still present, and checks that the final record count matches.
Review code changes against accepted Architecture Decision Records, documents that capture agreed design choices. Report violations, outdated references, compliant changes, and areas without ADR coverage, then suggest code fixes or a new decision record where appropriate.
Check saved architecture decision records (ADRs) for broken references, circular replacement relationships, and inconsistent statuses. Use the results to verify imported records or stop a CI check when selected integrity rules fail.