What makes cargo-analytics notable?

1.5K downloads. Trust evidence available

How should cargo-analytics be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

cargo-analytics

Get data out of Cargo and measure what ran — download a run output, export a segment or model to CSV or JSON, and pull run and batch success and error counts. Triggers: "download the results", "export this to CSV", "give me the file", "how many succeeded", "what is my error rate", "send me the enriched list", "get the output of that run", "how many records did it write". Skip when: asking why something failed or where credits went — use cargo-diagnostics; asking about credits, plans, or invoices — use cargo-billing.

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.5k

Updated

Oct 10, 2026

Version

1.6.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.5K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.5K downloadsadoption · observed Oct 10, 2026
Latest release: 1.6.0release · observed Sep 16, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s178dcd9wkfn0a2fqrygmt3jzn87j9e1:cargo-analytics

Install using `clawhub skill install s178dcd9wkfn0a2fqrygmt3jzn87j9e1:cargo-analytics` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/cargo-ai/cargo-analytics before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-cargo-ai-cargo-analytics/snapshot"

Documentation

CLAWHUB

146,451 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: cargo-analytics
description: "Get data out of Cargo and measure what ran — download a run output, export a segment or model to CSV or JSON, and pull run and batch success and error counts. Triggers: \"download the results\", \"export this to CSV\", \"give me the file\", \"how many succeeded\", \"what is my error rate\", \"send me the enriched list\", \"get the output of that run\", \"how many records did it write\". Skip when: asking why something failed or where credits went — use cargo-diagnostics; asking about credits, plans, or invoices — use cargo-billing."
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 — Analytics

Measurement and export: monitoring run metrics, downloading run and batch results, and exporting segment data.

> See `references/response-shapes.md` for full JSON response structures.
> See `references/troubleshooting.md` for common errors and how to fix them.
> See `references/examples/run-analytics.md` for run metrics and error monitoring.
> See `references/examples/exports.md` for data export and download examples.
> For billing, usage metrics, and subscription: use the `cargo-billing` skill.

## 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`. 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.

## Scope — measure and export, not explain

This skill answers **"what happened"** and **"give me the data"**: metrics, counts, downloads, exports. The moment the question becomes **"why"** — why did this run fail, why is the output wrong or empty, which root cause explains these errors, why is this play so expensive — switch to the `cargo-diagnostics` skill; its runbooks sequence the raw surfaces into a diagnosis.

| The question sounds like… | Load |
| --- | --- |
| "What's the error rate?" / "How many r

_meta.json

{
  "ownerId": "kn7by8t6yt9yghbxtxz6hv0bts87k6bq",
  "slug": "cargo-analytics",
  "version": "1.6.0",
  "publishedAt": 1789543554522
}

references/examples/exports.md

# Data export examples

## Download all finished runs

```bash
cargo-ai orchestration run download \
  --workflow-uuid <uuid> \
  --is-finished
```

## Download runs by status

```bash
# Only successful runs
cargo-ai orchestration run download \
  --workflow-uuid <uuid> \
  --statuses success

# Both success and error (for analysis)
cargo-ai orchestration run download \
  --workflow-uuid <uuid> \
  --statuses success,error

# Only error runs (for debugging)
cargo-ai orchestration run download \
  --workflow-uuid <uuid> \
  --statuses error
```

## Download runs in a date range

```bash
cargo-ai orchestration run download \
  --workflow-uuid <uuid> \
  --created-after 2025-01-01 \
  --created-before 2025-01-31
```

## Download runs from a specific batch

```bash
cargo-ai orchestration run download \
  --workflow-uuid <uuid> \
  --batch-uuid <batch-uuid>
```

## Download batch output by node

```bash
# 1. Get the batch and its release UUID
cargo-ai orchestration batch get <batch-uuid>
# → Extract releaseUuid

# 2. Find the output node slug
cargo-ai orchestration release get <release-uuid>
# → Read nodes[].slug — pick the output node's slug

# 3. Download
cargo-ai orchestration batch download \
  --uuid <batch-uuid> \
  --output-node-slug <node-slug>
```

## Export all segment data

```bash
# 1. List segments to find the modelUuid
cargo-ai segmentation segment list
# → Extract modelUuid (NOT segment uuid)

# 2. Full export
cargo-ai segmentation segment download \
  --model-uuid <model-uuid> \
  --filter '{"conjonction":"and","groups":[]}'
```

## Export segment data with sorting and limit

```bash
cargo-ai segmentation segment download \
  --model-uuid <model-uuid> \
  --filter '{"conjonction":"and","groups":[]}' \
  --sort '[{"columnSlug":"created_at","kind":"desc"}]' \
  --limit 5000
```

## Export filtered segment data

```bash
# Export only churned accounts
cargo-ai segmentation segment download \
  --model-uuid <model-uuid> \
  --filter '{
    "conjonction": "and",
    "groups": [{
      "conjonction": "and",
      "conditions": [
        {"kind": "string", "columnSlug": "status", "operator": "is", "values": ["churned"]}
      ]
    }]
  }'

# Export US companies with 100+ employees
cargo-ai segmentation segment download \
  --model-uuid <model-uuid> \
  --filter '{
    "conjonction": "and",
    "groups": [{
      "conjonction": "and",
      "conditions": [
        {"kind": "string", "columnSlug": "country", "operator": "is", "values": ["US"]},
        {"kind": "number", "columnSlug": "employee_count", "operator": "greaterThan", "value": 100}
      ]
    }]
  }'

# Export records created after a date
cargo-ai segmentation segment download \
  --model-uuid <model-uuid> \
  --filter '{
    "conjonction": "and",
    "groups": [{
      "conjonction": "and",
      "conditions": [
        {"kind": "date", "columnSlug": "created_at", "operator": "greaterThan", "value": "2025-01-01"}
      ]
    }]
  }'
```

## Export a segment with non-null email

```

references/examples/run-analytics.md

# Run analytics examples

## Get metrics for a workflow

```bash
cargo-ai orchestration run get-metrics --workflow-uuid <uuid>
```

Response:

```json
{
  "runMetrics": [
    {
      "nodeUuid": "node-uuid-1",
      "totalExecutionsCount": 1000,
      "successExecutionsCount": 950,
      "errorExecutionsCount": 30,
      "cancelledExecutionsCount": 5,
      "creditsUsedCount": 450
    }
  ]
}
```

Error rate per node = `errorExecutionsCount / totalExecutionsCount`. High error rate on a specific node means that step is failing.

## Metrics scoped to a specific release

```bash
cargo-ai orchestration run get-metrics \
  --workflow-uuid <uuid> \
  --release-uuid <release-uuid>
```

## Metrics scoped to a specific batch

```bash
cargo-ai orchestration run get-metrics \
  --workflow-uuid <uuid> \
  --batch-uuid <batch-uuid>
```

## Metrics for a date range

```bash
cargo-ai orchestration run get-metrics \
  --workflow-uuid <uuid> \
  --created-after 2025-01-01 \
  --created-before 2025-01-31
```

## Count errors

```bash
# Total error count
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --statuses error
```

Response:

```json
{ "count": 42 }
```

```bash
# Errors in a specific period
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --statuses error \
  --created-after 2025-01-15 \
  --created-before 2025-01-16

# Errors in a specific batch
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --statuses error \
  --batch-uuid <batch-uuid>
```

## Count finished runs

```bash
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --is-finished

# In a date range
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --is-finished \
  --created-after 2025-01-01 \
  --created-before 2025-01-31
```

## Count successful runs

```bash
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --statuses success
```

## Per-workflow cost analysis (full flow)

```bash
# 1. List workflows
cargo-ai orchestration workflow list

# 2. Get usage grouped by workflow
cargo-ai billing usage get-metrics \
  --from 2025-01-01 --to 2025-01-31 \
  --group-by workflow_uuid

# 3. Drill into a specific workflow
cargo-ai billing usage get-metrics \
  --from 2025-01-01 --to 2025-01-31 \
  --workflow-uuid <uuid>

# 4. Get run-level metrics
cargo-ai orchestration run get-metrics \
  --workflow-uuid <uuid> \
  --created-after 2025-01-01 \
  --created-before 2025-01-31
```

## Error monitoring and debugging (full flow)

```bash
# 1. Count errors
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --statuses error

# 2. Spot-check: count errors in the last 24 hours
cargo-ai orchestration run count \
  --workflow-uuid <uuid> \
  --statuses error \
  --created-after 2025-01-15 \
  --created-before 2025-01-16

# 3. Download error runs for inspection
cargo-ai orchestration run download \
  --workflow-uuid <uuid> \
  --statuses error \
  --created-after 2025-01-15

# 4. Check per-node error rates
cargo-ai orch

references/response-shapes.md

# Response shapes

JSON response structures returned by Cargo CLI commands used in the `cargo-analytics` skill.

> For billing response shapes (usage metrics, subscription, invoices), see the `cargo-billing` skill.

## cargo-ai orchestration run get-metrics

```json
{
  "runMetrics": [
    {
      "nodeUuid": "node-uuid-1",
      "totalExecutionsCount": 1000,
      "idleExecutionsCount": 0,
      "pendingExecutionsCount": 5,
      "runningExecutionsCount": 10,
      "successExecutionsCount": 950,
      "errorExecutionsCount": 30,
      "cancelledExecutionsCount": 5,
      "skippedExecutionsCount": 0,
      "creditsUsedCount": 450
    }
  ]
}
```

**Key fields:** `nodeUuid` (identifies the workflow node), `successExecutionsCount`, `errorExecutionsCount`, `creditsUsedCount`.

To compute an error rate: `errorExecutionsCount / totalExecutionsCount`.

## cargo-ai orchestration run count

```json
{
  "count": 42
}
```

## cargo-ai orchestration run list

```json
{
  "runs": [
    {
      "uuid": "run-uuid",
      "workflowUuid": "...",
      "status": "success",
      "batchUuid": "batch-uuid-or-null",
      "releaseUuid": "...",
      "recordId": "rec-123",
      "recordTitle": "Acme Corp",
      "createdAt": "2025-01-15T10:00:00Z",
      "finishedAt": "2025-01-15T10:00:05Z"
    }
  ]
}
```

## cargo-ai segmentation segment download

Returns raw data as a downloadable payload (typically CSV or JSON depending on the CLI output format). The response is streamed to stdout.

## cargo-ai orchestration batch download

Returns `{"url": "..."}` — a signed URL to a file, **not** the data on stdout. Each row is a batch record joined to its run's output for the chosen node (defaulting to the last executed node), so a record whose run errored comes back with its input fields and no output.

## cargo-ai orchestration run download

Returns `{"url": "..."}` — a signed URL to a **gzipped CSV**. One row per run: `_uuid`, `_workspace_uuid`, `_workflow_uuid`, `_record_id`, `_record_title`, `_created_at`, `_finished_at`, `_status`, `_error_message`, then one column per node slug holding that execution's `title` (a truncated summary, not the node's output). No `runContext`, no `executions[]`.

## cargo-ai orchestration run download-outputs

Returns `{"url": "..."}` — a signed URL to CSV (default) or JSON. One row per run: the `_`-prefixed run metadata above, plus `input` (first node's resolved config) and `output` (chosen node's context, defaulting to the last executed node).

Github ReposUpdated 19h agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.