Skill Detail

Debug and Trace Configuration

This skill helps set up debugging and tracing tools. It provides documentation on how to configure debugging workflows and implement tracing solutions.

GitHub:sickn33/antigravity-awesome-skills distributed-debugging-debug-trace
version cf4e66dd52d7
static analysis only
no human review yet
Use Caution

Current public label

Use Caution

Because the skill references secrets and external endpoints, you should use caution when deploying it.

This label is currently coming from the automated scorecard.

Automated result

Use Caution

Driftloom found that this skill's source code is mostly documentation, and that the documentation mentions secrets and external network endpoints.

3 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
94
Quality
94
Transparency
94
Operational
92
Maintenance
82

3 low Final label: use caution.

Severity mix: 3 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 secret, token, password, and credential references.
  • 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
Secret or credential reference detected
secret.reference · safety
Low

The docs mention credentials or secrets. That may be normal, but it still tells you the skill expects sensitive material somewhere in the workflow.

File: resources/implementation-playbook.md
Evidence: token
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: resources/implementation-playbook.md
Evidence: http://localhost:14268/api/traces
Driftloom is following the boring, correct architecture: Django control plane first, isolated runner later. Miraculously, restraint survives.