Files
AgentHub/plugins/agenthub-insights/skills/regression-watch/SKILL.md
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nntrivi2001 17d56d0e01 refactor!: rebrand CCAM to AgentHub
Clean break, no compatibility alias. Renames the product name, the CLI
binary (`ccam` -> `agenthub`), the env var prefix (`CCAM_` ->
`AGENTHUB_`), the Prometheus metric namespace (`ccam_*` ->
`agenthub_*`), the tmux session prefix (`ccam-lane-<id>` ->
`agenthub-lane-<id>`), the per-repo runtime profile directory
(`.ccam/profile` -> `.agenthub/profile`), the lanes state root
(`~/.claude/ccam-lanes` -> `~/.claude/agenthub-lanes`), the bundled
plugins (`plugins/ccam*` -> `plugins/agenthub*`) and their slash
commands (`/ccam-doctor` -> `/agenthub-doctor`, `/ccam:*` ->
`/agenthub:*`).

Because there is no alias, an existing install has to be updated by
hand: rename its `.ccam/profile` directory and any `CCAM_*` variables,
and reinstall the plugin under its new name.

Two other name families are deliberately left alone here, since they are
not just strings: the `Claude-Code-Monitor` repository/marketplace name,
and the `agent-dashboard` npm package plus its `~/.claude/agent-dashboard`
runtime directory, which holds the live database and needs a migration
rather than a rename.

Verified: server 1406/1406, client 459/459, `grep -i ccam` clean across
tracked files, `openapi.yaml` regenerated (95 paths, unchanged count).
2026-09-07 12:09:15 +07:00

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---
description: >
Detect quality and efficiency regressions over time using Agent Monitor data —
rising error rate (APIError events), falling cache hit rate, growing compaction
frequency, and climbing cost-per-session. Splits history into an earlier
baseline window and a recent window and reports which metrics are getting
worse, by how much, and where. Use when checking whether things are degrading
or trending in the wrong direction.
---
# Regression Watch
Detect whether Claude Code sessions are getting worse over time across quality and
efficiency metrics, using Agent Monitor data.
## Input
The user provides: **$ARGUMENTS**
This may be:
- empty or "all" — check every regression metric (default)
- "errors" — error-rate regression only
- "cache" — cache hit-rate regression only
- "compaction" — compaction-frequency regression only
- "cost" — cost-per-session regression only
- A window like "last 30d" or "30 vs 90" — set the recent vs baseline window sizes
## Data Sources
| Endpoint | Returns |
|----------|---------|
| `GET /api/analytics` | `daily_events` (365d), `daily_sessions` (365d), `event_types`, `tokens` (total_input, total_output, total_cache_read, total_cache_write — baselines pre-summed), `avg_events_per_session` |
| `GET /api/events?session_id=X` | Event stream incl. `APIError`, `Compaction`, `PreToolUse`/`PostToolUse` — used to localize regressions to specific sessions |
| `GET /api/pricing/cost` | `{ total_cost, breakdown[...] }` — total cost to derive cost-per-session |
| `GET /api/pricing/cost/{sessionId}` | Per-session cost — used to compare recent vs baseline session cost |
| `GET /api/workflows/{sessionId}` | `compaction` (impact), `errorPropagation` (by depth), `effectiveness` — per-session quality signals |
| `GET /api/sessions?limit=N` | Sessions with `started_at`, `cost`, `metadata` — to bucket sessions into time windows |
## Report Sections
### 1. Windowing
Split history into a **baseline window** (older) and a **recent window** (newer).
Default: recent = last 30 days, baseline = the 30–90 day range before it. Use
`daily_events`/`daily_sessions` for series metrics and `GET /api/sessions?limit=N`
to assign sessions to each window by `started_at`.
### 2. Error Rate Regression
- Recent error rate = `APIError count / total events` in the recent window
(from `event_types` and `daily_events`, or per-session `GET /api/events`).
- Compare to the baseline rate. Flag if recent is higher.
- Report the absolute and relative change and which sessions contributed most
`APIError` events.
### 3. Cache Hit Rate Regression
- Cache hit rate = `total_cache_read / (total_cache_read + total_input)`.
- Compute for each window (per-window input/cache_read from session metadata or
the pricing breakdown). Flag a **falling** hit rate — that means more
uncached input tokens and higher cost.
### 4. Compaction Frequency Regression
- Compaction frequency = `Compaction events / session` per window (from
`event_types` / `daily_events`, confirmed via per-session
`GET /api/workflows/{id}` `compaction`). Flag a **rising** rate — context is
overflowing more often.
### 5. Cost-per-Session Regression
- Cost-per-session = window total cost / window session count, using
`GET /api/pricing/cost` overall and `GET /api/pricing/cost/{id}` for the
sessions in each window. Flag a **climbing** value.
### 6. Verdict
Roll up which metrics regressed, rank by relative worsening, and name the most
likely driver (e.g., cache hit rate fell → cost per session climbed).
## Output
- A Markdown table: metric | baseline | recent | Δ | direction (▲ worse / ▼ better) | verdict.
- Tag each regressed metric 🔴 (clear regression), 🟡 (mild/within noise), or 🟢 (improved).
- Currency in USD to 4 decimals; rates as percentages to 2 decimals.
- List the specific session IDs that contributed most to any regression.
- End with the single highest-priority regression to address and a concrete next step.
- Read-only: only report what the API returns; never fabricate baselines.