AD terraform-skill
Diagnoses and designs safe Terraform releases, provisioners, multi-environment isolation, and fresh-host bootstrap. Use when writing or reviewing plan/apply wrappers, null_resource, remote-exec, local-exec, file provisioners, cloud-init, Docker Compose or Caddy deployment; when staging and production configuration may differ; when an IaC rollout can mutate a shared gateway; or when debugging drift, saved-plan, provenance, TLS, Restarting/unhealthy containers, DNS duplication, snapshot contamination, and post-apply failures. It emphasizes exact reviewed artifacts, pre-mutation validation, explicit production authorization, and independent live readback.
Diagnoses and designs safe Terraform releases, provisioners, multi-environment isolation, and fresh-host bootstrap.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 24 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 27 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3399 tokens
- 100Progress reporting. Reports progress
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 660: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 27 items
- +4Has examples (13 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.