Skill Detail

Hybrid Search Implementation

This skill provides documentation about implementing hybrid search, combining vector similarity and keyword-based search.

GitHub:sickn33/antigravity-awesome-skills hybrid-search-implementation
version 2b08dc3df1f4
static analysis only
no human review yet
Use Caution

Current public label

Use Caution

Because the skill makes network calls, it is labeled with caution. The documentation-heavy structure limits how much automation can verify.

This label is currently coming from the automated scorecard.

Automated result

Use Caution

The skill's documentation includes code that makes network calls. The skill's structure is mostly documentation.

1 medium, 1 low Final label: use caution.

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
85
Operational
92
Maintenance
76

1 medium, 1 low Final label: use caution.

Severity mix: 1 medium, 1 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

Programmatic network client usage detected
network.client_code · transparency
Medium

The source appears to make outbound HTTP calls in code.

File: resources/implementation-playbook.md
Evidence: fetch(
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
Driftloom is following the boring, correct architecture: Django control plane first, isolated runner later. Miraculously, restraint survives.