BB exec-env-check
Check the local execution environment for GPU availability, Docker support, and Slurm access. Returns the execution scenario (`satisfied, local, docker`, `satisfied, local, direct`, `satisfied, slurm, local`, or `not_satisfied`), the number of available GPUs, and the GPU type. On Slurm login nodes without local GPUs, the cluster is identified by delegating the hostname to internal-env-info (hostname-based mode), which owns the hostname → cluster_name patterns; GPU type and gpus_per_node then come from that skill's reference files. If internal-env-info is not installed, the scenario falls back to `not_satisfied` without probing compute nodes via srun.
Checks where the code will run: local GPU, Docker, Slurm, or nowhere. Returns execution scenario, GPU count, and type. On Slurm login nodes without local GPUs, delegates to internal-env-info; if that skill is missing, falls back to not_satisfied without probing compute nodes.
One file, linter clean, safety 100. Quality 76 and process 70 suggest sparse tests or usage docs. No critical bugs, but logic depends on a sibling skill. Works for Slurm environments if internal-env-info is already installed; otherwise the skill just gives up.
Install if you need automatic environment diagnostics before launching heavy workloads. Without internal-env-info on a Slurm cluster, limited value.
Check the local execution environment for GPU availability, Docker support, and Slurm access.
As a process B 70/100 · Nearly there — weak spots: when it triggers, progress reporting
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 70/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 16 steps, 1 vague phrases
- 100Failures and branches. 5 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1329 tokens
- 100Running it twice. No mutating operations
- low The response is described with custom markup (3 tags): a typed call is more reliable
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)
- +2Single-language instructions
- +3Description length 658: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 16 items
- +3Output format is stated explicitly
- +4Has examples (9 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.