AC agent-cli-builder
Build or modernize TypeScript CLIs for AI agents with @renxqoo/agent-cli-sdk. Use when a user wants a new command-line tool, an API or internal service wrapped as a CLI, or an existing agent-cli-sdk app extended with authentication, structured output, typed errors, pagination, pipes, Skill distribution, or tests. Do not use for generic shell scripts, non-CLI applications, or tasks that explicitly require another CLI framework.
Build or modernize TypeScript CLIs for AI agents with @renxqoo/agent-cli-sdk.
As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Concealment
en-hide-from-userreferences/core-api.md:21Instruction to hide actions from the user (negated — the text forbids it)- Do not silently install global dependencies or copy `@latest` blindly.
negated
Files scanned: 14. 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 60/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 5 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 55 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2945 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (5 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
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 430: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 55 items
- +4Reference files are cited in the instructions (11 of 11)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.