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.
58 lines
3.0 KiB
Markdown
58 lines
3.0 KiB
Markdown
---
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description: >
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Scan recent Claude Code activity for errors and failure signals across all
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sessions using Agent Monitor data — APIError events and PreToolUse→PostToolUse
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gaps (tools that started but never completed) — then group failures by tool and
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model and rank them by frequency. Use when checking for errors or asking
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"what's failing right now".
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---
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# Error Scan
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Sweep recent events across sessions for error and failure signals, then rank them
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by how often they occur and which tool or model produced them.
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## Input
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The user provides: **$ARGUMENTS**
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This may be:
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- empty or "all" — scan every failure signal (default)
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- "api" — APIError events only
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- "tools" — tool-failure gaps only
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- a number N — limit the scan to the most recent N sessions
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- a session ID — scan a single session
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## Data Sources
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| Endpoint | Returns |
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|----------|---------|
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| `GET /api/analytics` | `event_types` (counts per type incl. PreToolUse, PostToolUse, APIError), `tool_usage` (top 20), `daily_events` (365d) — fleet-wide failure baseline |
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| `GET /api/events?session_id=X` | Per-session event stream: `event_type`, `tool_name`, `summary`, `data`, `timestamp` — locate `APIError` and unmatched `PreToolUse` |
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| `GET /api/sessions?limit=N` | Sessions with `id`, `status`, `model`, `started_at` — pick the recent window and attribute failures to a model |
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## Report Sections
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### 1. Scope
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Resolve `$ARGUMENTS` to a session set: pull `GET /api/sessions?limit=N` (default 50, ordered by `started_at`). Report how many sessions and what time span are covered.
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### 2. Fleet Failure Counts
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From `GET /api/analytics` `event_types`, report total `APIError` count and the PreToolUse→PostToolUse gap: `gap = PreToolUse − PostToolUse` (unmatched tool starts = likely failures). State both as raw counts and as a share of `total_events`.
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### 3. Group by Tool
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For each session in scope, pull `GET /api/events?session_id=X`. Match each `PreToolUse` to its following `PostToolUse` by `tool_name`; unmatched starts are failures. Aggregate failures and `APIError` events per `tool_name`. Rank tools by failure frequency (descending).
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### 4. Group by Model
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Join failures to the owning session's `model` (from `GET /api/sessions`). Rank models by APIError count and tool-failure count.
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### 5. Top Offenders
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List the single most failure-prone tool, the most error-prone model, and the session with the most failures, each with its exact count and one-line `summary` excerpt from a representative event.
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## Output
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- A ranked Markdown table: tool/model | APIError count | tool-failure (gap) count | total failures | share of events.
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- Rates as percentages to 2 decimals.
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- Cite exact `event_type`, `tool_name`, and `session_id` values — never fabricate counts.
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- End with the one failure pattern most worth investigating and a concrete next step.
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- Read-only: only report what the API returns. If `curl` cannot reach `http://localhost:4820`, tell the user to start the dashboard with `npm start` from the repo root.
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