Skill Detail

Bazel Build Optimization

This skill provides documentation about Bazel build optimization in large-scale monorepos.

GitHub:sickn33/antigravity-awesome-skills bazel-build-optimization
version 32106de7ea89
static analysis only
no human review yet
Trusted

Current public label

Trusted

The skill is mostly documentation, and the external network reference is not inherently harmful, so the automated label is appropriate.

This label is currently coming from the automated scorecard.

Automated result

Trusted

Driftloom found that this skill is mostly documentation and references external endpoints.

2 low Final label: trusted.

Human review

No human review has been recorded yet.

The current public label is still relying on automation. A human has not weighed in yet.

What happened

Driftloom completed a static scan. It inspected the skill files, recorded findings, and generated a scorecard.

Runtime evidence

No sandbox runtime result has been recorded yet.

What did not happen

  • Driftloom did not run this skill in an isolated sandbox yet.
  • This label is not a guarantee that the skill is safe, bug-free, or appropriate for every environment.
  • A good score does not replace human judgment when a skill touches secrets, shell access, or external systems.

Source provenance

Source: Workspace import

Originally ingested from a local workspace copy.

Scorecard

Safety
100
Quality
94
Transparency
94
Operational
92
Maintenance
82

2 low Final label: trusted.

Severity mix: 2 low

What Driftloom checked

  • Read the skill files and metadata to understand what the skill claims to do.
  • Looked for shell commands and risky command patterns, even if none stood out strongly.
  • Looked for external URLs, network calls, and signs the skill reaches outside the machine.
  • Looked for secrets and credential handling clues.
  • Checked whether the skill structure and references looked internally consistent.

Findings

Documentation-only skill structure
structure.docs_only · quality
Low

The source looks almost entirely documentation-based, with no obvious code or config files to inspect. That does not make it bad, but it limits how much automation can meaningfully verify.

File: SKILL.md
Explicit external endpoint reference detected
network.url_reference · transparency
Low

The docs reference an external endpoint or network flow in a context that likely matters to how the skill operates.

File: SKILL.md
Evidence: https://github.com/aspect-build/rules_js/releases/download/v1.34.0/rules_js-v1.34.0.tar.gz
Driftloom is following the boring, correct architecture: Django control plane first, isolated runner later. Miraculously, restraint survives.