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dprakash2101dprakash2101/dotnet-production-agent-skills/skills/google-bigquery-dotnet/SKILL.md

google-bigquery-dotnet

Skill4 starsChanged 52 days agoMITView on GitHub

Use when implementing, modifying, reviewing, troubleshooting, or optimizing Google BigQuery integrations in .NET, including BigQueryClient, authentication, parameterized queries, DATE/DATETIME/TIMESTAMP types, query costs, serialization, and result mapping.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Follow existing integration/data-access boundaries and the installed Google.Cloud.BigQuery.V2 version.

    line 8
  2. Distinctive:

    Use parameterized Standard SQL for every untrusted or runtime value.

    line 10
  3. Distinctive:

    Before finalizing, inspect estimated/scanned bytes or repository query safeguards when available, and test mapping boundaries, nulls, …

    line 21
  4. Distinctive:

    Read references/query-safety.md for job, pagination, and date/time decision details.

    line 23

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Google BigQuery for .NET

Follow existing integration/data-access boundaries and the installed Google.Cloud.BigQuery.V2 version. Reuse BigQueryClient according to repository lifetime conventions. Authenticate with Application Default Credentials and deployed workload/service identities; never embed service-account keys.

Use parameterized Standard SQL for every untrusted or runtime value. Never concatenate values into SQL. Identifiers cannot generally be value parameters, so select them only from an explicit trusted allowlist when dynamic identifiers are unavoidable.

  • Select named columns rather than SELECT *. Apply partition filters and clustering-compatible predicates, and avoid scanning repeated data. Query design directly affects cloud cost.
  • Choose immediate query execution versus explicit query jobs based on existing patterns and whether job ID, polling, labels, destination tables, or long-running lifecycle control is needed.
  • Pass cancellation through async job creation/result retrieval where supported. Do not block async calls or add polling loops when the client already provides completion behavior.
  • Page or stream results and project only required data. Do not call materializing helpers for an unbounded or potentially large result set; cap exports and use destination tables/storage workflows when appropriate.
  • Map nulls deliberately and validate schema/type assumptions. Treat BigQuery TIMESTAMP as an absolute instant and DATETIME as a timezone-free civil value; do not silently convert between them using a machine-local timezone.
  • Classify API, quota, permission, invalid-query, timeout, and cancellation failures. Preserve useful job/correlation IDs in safe structured logs, but do not log credentials, full sensitive SQL, or parameter values by default.

Do not add custom query/job retries merely because failures can be transient. Add them only when explicitly requested or required by existing architecture, prefer client/platform resilience, and account for job identity, duplicate submission, cost, timeout budget, bounded attempts, cancellation, and ambiguous completion. Never retry permission, invalid-query, or other permanent failures.

Before finalizing, inspect estimated/scanned bytes or repository query safeguards when available, and test mapping boundaries, nulls, pagination, cancellation, and date/time semantics relevant to the query.

Read references/query-safety.md for job, pagination, and date/time decision details.

Where supported by the installed client and repository, use query dry runs or maximum-bytes controls to bound cost. Preserve job identity when investigating ambiguous completion.

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