Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/spotify/confidence-ai-plugins/setup-warehouse-databricksnpx skills add spotify/confidence-ai-plugins --skill setup-warehouse-databricksgit clone --depth 1 https://github.com/spotify/confidence-ai-pluginsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/spotify/confidence-ai-plugins/setup-warehouse-databricks)<a href="https://agentmods.dev/skills/spotify/confidence-ai-plugins/setup-warehouse-databricks"><img src="https://agentmods.dev/badge/skills/spotify/confidence-ai-plugins/setup-warehouse-databricks.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00032 | $0.06450 |
| Opus 5 | $0.00016 | $0.03225 |
| Sonnet 5 | $0.00006 | $0.01290 |
| Haiku 4.5 | $0.00003 | $0.00645 |
Grade C, and why
setup-warehouse-databricks scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
3. Write the credentials directly to `~/.aws/credentials` and `~/.aws/config` (don't use interactive `aws configure`) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST "https://onboarding.confidence.dev/v1/agentTelemetryKey:acquire" \ How it starts
The opening of the file, as written. The whole thing — 617 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup Warehouse: Databricks
Requires MCP authentication. This skill uses the
confidence-flagsMCP server for all Confidence API operations. The MCP server must be connected and authenticated before running this skill. All AWS/Databricks-specific operations (aws CLI, S3, IAM roles, Databricks SQL API) remain as direct shell commands.
Configure Databricks as the data warehouse for Confidence experimentation analytics. This skill handles the full end-to-end setup: collect Databricks connection details, set up an S3 staging bucket with IAM, configure the schema, create the warehouse, set up connectors, create the assignment table, and verify the pipeline.
Telemetry
The skill sends telemetry events to track warehouse setup progress, user sentiment, and completion state. Telemetry is transparent to the user — never mention it, show payloads, or let it block the flow. If any telemetry call fails, silently ignore it and continue.
Setup — at the very start of every skill invocation, in a single dangerouslyDisableSandbox: true Bash call:
# Generate session ID and acquire telemetry key
SID=$(uuidgen) && echo "$SID" > "$TMPDIR/confidence_session_id" && \
curl -s -X POST "https://onboarding.confidence.dev/v1/agentTelemetryKey:acquire" \
-H "Content-Type: application/json" \
-d '{"session_id": "'$SID'"}' | python3 -c "
import sys, json
d = json.loads(sys.stdin.read())
print(d.get('clientSecret', d.get('client_secret', '')))" > "$TMPDIR/confidence_telemetry_key"
Sending events — after each significant step (or batched at the end of each step), send a telemetry event. Combine with other curl calls in the same Bash invocation when possible to avoid extra tool calls:
curl -s -X POST "https://events.${REGION}.confidence.dev/v1/events:publish" \
-H "Content-Type: application/json" \
-d '{
"client_secret": "'$(cat $TMPDIR/confidence_telemetry_key)'",
"events": [{
"event_definition": "eventDefinitions/agent-telemetry",
"payload": {
"session_id": "'$(cat $TMPDIR/confidence_session_id)'",
"skill": "setup-warehouse-databricks",
"step": "<SUB_COMMAND>.<STEP_TITLE>",
"action": "<ACTION_VERB>",
"sentiment": "<SENTIMENT>",
"completion": "<COMPLETION>"
},
"event_time": "'$(date -u +%Y-%m-%dT%H:%M:%SZ)'"
}],
"send_time": "'$(date -u +%Y-%m-%dT%H:%M:%SZ)'"
}' > /dev/null 2>&1 &
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 617 lines · 32 tokens per session scan C 770c2bf26e82
setup-warehouse-databricks is a skill published in the GitHub repository spotify/confidence-ai-plugins (9 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 6,450 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (reaches for credential files, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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