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cargo-diagnostics — Claude Code skill: debug Cargo runs

A skill that explains what a Cargo run or batch actually did: which node broke, what failed in the batch, and where the credits went.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add getcargohq/cargo-skills --skill cargo-diagnostics -a claude-code
Open on GitHub

What cargo-diagnostics does

The skill walks one run node by node, draws the executed graph and marks the step that failed. For a batch that keeps erroring, it sweeps the whole thing and groups failures by root cause. A third runbook covers spend, attributing credits down to the node and the provider.

Each runbook says which surface to pull and in what order. cargo-ai orchestration run get <run-uuid> returns run.executions[] and runContext; the trace and span commands expose failures without SQL; cargo-ai orchestration query execute "<sql>" gives aggregates. No run UUID to start from? The skill resolves a symptom to one first.

You need @cargo-ai/cli from npm and a signed-in account: cargo-ai login --email mails a code, with --oauth and --token for CI as alternatives. Cost attribution through billing usage get-metrics and billing subscription get demands a token with admin access. A standard token still gets you traces and error sweeps, just not the spend breakdown — worth confirming before anyone asks for a budget report.

What it helps with

  • trace a failed run node by node
  • find the root cause behind a batch's errors
  • draw the execution graph with the failing node marked
  • explain blank columns in a run that reported success
  • break credit spend down to node and provider

Example prompts for the agent

  • Walk run 9f3c2a node by node and tell me where it broke
  • Half the rows in this batch are empty — group the errors by root cause
  • Why is this play so expensive? Show credit spend per node

How to install cargo-diagnostics

1Skills CLI (Vercel)

npx skills add getcargohq/cargo-skills --skill cargo-diagnostics -a claude-code

2Manually: put the files in place

~/.claude/skills/cargo-diagnostics/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/cargo-diagnostics/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about cargo-diagnostics

How do I install cargo-diagnostics in Claude Code?

Run npx skills add getcargohq/cargo-skills --skill cargo-diagnostics -a claude-code; the skill file then sits at ~/.claude/skills/cargo-diagnostics/SKILL.md.

What does cargo-diagnostics do?

It explains after the fact what a Cargo run or batch did: per-node traces, failures grouped by cause, and credit attribution. It is an interpretation layer over the CLI rather than a separate engine.

What does it need to work?

@cargo-ai/cli installed and a signed-in account. Per-node cost breakdown requires an admin token; with a standard token you get tracing and error sweeps only.

Source text

SKILL.md · MIT
---
name: cargo-diagnostics
description: "Explain what a Cargo run or batch actually did, after the fact — trace one run node by node, draw the graph it executed with the failing step marked, sweep a batch or play for errors grouped by root cause, and attribute credit spend down to the node and the provider. Triggers: \"why did this fail\", \"it succeeded but the output is wrong\", \"half my rows are empty\", \"why is this column blank\", \"what broke in this batch\", \"why did that cost so much\", \"which node is burning credits\", \"it worked yesterday\", \"these results look wrong\", \"it went down the wrong path\", \"this step never ran\", \"show me what the run did\". Skip when: setting up an alert for next time — use cargo-observability; just downloading the data — use cargo-analytics."
version: "1.6.0"
compatibility: Requires @cargo-ai/cli (npm). Sign in or create an account with `cargo-ai login --email` (emailed code, no browser), `--oauth`, or an API token
homepage: https://github.com/getcargohq/cargo-skills
metadata:
  author: getcargo
  openclaw:
    requires:
      bins:
        - cargo-ai
    install:
      - kind: node
        package: "@cargo-ai/cli@latest"
        bins:
          - cargo-ai
    homepage: https://github.com/getcargohq/cargo-skills
---

# Cargo CLI — Diagnostics

Forensic runbooks for workflow behavior: trace one run, sweep a batch for errors, profile a play's credit spend. This skill is the **interpretation layer** — the raw surfaces (`run get`, orchestration SQL, billing metrics) are documented in `cargo-orchestration` and `cargo-billing`; each runbook here tells you which of them to pull, in what order, and what each output shape means.

## Bootstrap

Already signed in (`cargo-ai whoami` returns a workspace)? Skip to the next section.

```bash
npm install -g @cargo-ai/cli            # no global install? prefix every command with `npx @cargo-ai/cli`
cargo-ai login --email [email protected]  # emailed code, no browser; creates the account on first use
                                        # alternatives: --oauth (browser) · --token <api-token> (CI)
cargo-ai whoami                         # confirm the active workspace before any write
```

Every command prints JSON to stdout; failures exit non-zero with `{"errorMessage": "..."}`. Anything that creates a run or a batch is async — pass `--wait-until-finished` or poll the matching `get`. Credit attribution steps (`billing usage get-metrics`, `billing subscription get`) need a token with **admin access**; everything else works with a standard token. When the full skill bundle is installed, [`../cargo/references/prerequisites.md`](../cargo/references/prerequisites.md) adds the CLI version pin, token scopes, and the admin-only surface.

## Which runbook?

```
What are you diagnosing?
│
├── One run / one record ("why did this record fail?",
│   "run succeeded but the output is wrong/empty")
│   └── references/run-trace.md
│
├── Many runs ("the batch has errors", "error rate spiked",
│   "which node keeps failing?")
│   └── references/batch-error-sweep.md
│
└── Cost ("this play is expensive", "where do the credits go?",
    "make this cheaper")
    └── references/play-optimize-credits.md
```

Rule of thumb: start with the **sweep** when you don't yet know which run to look at — it ends by handing you exemplar run UUIDs to feed into the **trace**.

**No run UUID at all** ("look at the last run", "the run for acme.com", "what did my play do in the editor")? That's [`references/run-trace.md`](references/run-trace.md) § 0, which resolves a symptom to a UUID. Note that `orchestration run list` without `--workflow-uuid` needs `--created-after` and a window of at most 30 days, so it cannot answer "the last run" on its own; orchestration SQL over `runs` takes no filter and can. Never conclude that run inputs and outputs are inaccessible because `run list` refused.

**Boundary with `cargo-analytics`:** analytics *measures and exports* ("what's the error rate?", "download the batch results", "export this segment"); this skill *explains* ("why is the error rate up?", "why is this record's output empty?"). A diagnosis often starts from an analytics signal (error count spiked, batch reports `failedRunsCount > 0`) and ends back in analytics — once the cause is fixed and runs re-executed, bulk retrieval goes through `run download-outputs` / `batch download` / `segment download`, all documented in `../cargo-analytics/SKILL.md`. This skill's evidence surfaces (`run get`, orchestration SQL, billing metrics) are for diagnosis, not bulk export.

## References

| Doc | What it covers |
| --- | --- |
| [`references/run-trace.md`](references/run-trace.md) | Find a run from a symptom when you have no UUID (§ 0), then walk it end-to-end: per-node executions, `runContext` outputs, branch routing, per-node credits and timing. |
| [`references/batch-error-sweep.md`](references/batch-error-sweep.md) | Find errored runs across a batch/play/workspace, group failures by root cause, pick exemplars, decide fix vs report. |
| [`references/play-optimize-credits.md`](references/play-optimize-credits.md) | Attribute credit spend to workflows and nodes, then apply the cost levers in priority order. Attributes the **execution charge** separately (§ 2b) — 0.01 credits per node execution, which `creditsUsedCount` does not carry and per-node attribution therefore misses. |

## The surfaces every runbook draws on

| Surface | Command | Gives you |
| --- | --- | --- |
| Run detail | `cargo-ai orchestration run get <run-uuid>` | `run.executions[]` (node-by-node trace), `runContext` (per-node output keyed by `nodeSlug`), `runComputedConfigs` (what each node was actually called with) |
| Traces | `cargo-ai orchestration trace list --started-after <iso> [--statuses error,degraded] [--workflow-uuid <uuid>]` · `trace count` (same filters) · `trace get <trace-uuid>` | One row per **trace** — everything one trigger set off across the run lineage (tool and agent child runs, hosted-worker invocations, a chat's assistant turns): `status` (`pending`/`error`/`degraded`/`success`), `rootRunUuid`, `rootRecordTitle`, `spansCount`, `failedSpansCount`, `creditsUsedCount`, `workerUuid`, `chatUuid`. `--started-after` is **required**. `trace get` returns the aggregate only — no spans |
| Spans | `cargo-ai orchestration span list --execution-started-after <iso> [filters]` · `span count` (same filters, minus `--search`/`--limit`) | Node executions without SQL. Filters: `--batch-uuid`, `--run-uuid`, `--parent-run-uuid`, `--workflow-uuid`, `--execution-statuses pending,success,error`, `--node-action-slug`, `--node-integration-slug`, `--node-slug`, `--node-kind native\|connector\|tool\|agent\|worker`, `--execution-title-or-error-message <ilike>`, `--record-title-or-id`, `--search` (list only: record title/id, execution title or error). `--execution-started-after` is **required** |
| Orchestration SQL | `cargo-ai orchestration query execute "<sql>"` | Aggregates over `runs`, `batches`, `spans`, `records` (ClickHouse; no schema prefix; workspace-scoped). The one way to list a trace's spans by id: `WHERE trace_uuid = '<uuid>'` |
| Billing metrics | `cargo-ai billing usage get-metrics --from <date> --to <date>` | Credit totals, filterable and groupable by `workflow_uuid`, `connector_uuid`, `agent_uuid`, `integration_slug`, `model_uuid` |
| Graph picture | `cargo-ai orchestration node diagram --run-uuid <uuid> --highlight <slug> --format ascii --raw` | The graph the run executed, with the failing node marked. Free, runs nothing |

**Draw the graph before explaining a routing bug.** For "it took the wrong branch"
or "this step never ran", the picture is the evidence, and it shows one thing
`run get` does not make obvious: the `on failure` edges. A step that looks skipped
is often one the run *reached* via a `fallbackChildUuid` edge, which means the
provider errored rather than returning nothing — a different diagnosis with a
different fix. Flags and the ASCII legend: [`../cargo-orchestration/references/node-diagram.md`](../cargo-orchestration/references/node-diagram.md).

**`degraded` is not `success`.** A trace is `degraded` when a root-run node errored and a `fallbackOnFailure` / fallback edge carried the run to completion — the run reports success, the failed span stays `error`. `error` means an errored root-run node with no next node stopped it. Child-run failures don't settle a trace's status; `pending` means any span at any depth is still running. Sweep `--statuses error,degraded` together: a degraded trace is a provider failure the graph absorbed, usually the same root cause as the errors.

Full query syntax, table columns, and caps: [`../cargo-orchestration/references/examples/queries.md`](../cargo-orchestration/references/examples/queries.md). Debugging field semantics: [`../cargo-orchestration/references/troubleshooting.md`](../cargo-orchestration/references/troubleshooting.md).

## Presenting findings

Follow [`../cargo/references/interaction.md`](../cargo/references/interaction.md): lead with the conclusion ("18 of 20 failures are one cause: the connector's token expired"), summarize evidence in a short table, never dump raw `run get` JSON or full query results into the conversation. Any fix that re-runs paid nodes goes through the pilot gate: re-run **10–20 records** first, report the observed cost and hit-rate, then ask the user to approve the rest quoting the **record count** and **credit estimate** — a diagnosis is not approval to re-bill the batch that produced it. Full spend rules in [`../cargo-gtm/references/cost-discipline.md`](../cargo-gtm/references/cost-discipline.md).

## When diagnosis dead-ends

If the evidence contradicts documented behavior (a field missing from `run get`, a query cap that doesn't match the docs, an error that makes no sense), file a report — that's the official channel and the team reads every one:

```bash
cargo-ai workspaceManagement report create \
  --title "<one-line summary>" \
  --description "<commands run, errorMessage verbatim, expected vs actual, UUIDs>"
```

© getcargo · MIT · getcargohq/cargo-skills

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