BD ai-dev-runtime
Boost development efficiency with AI Dev Runtime, a comprehensive toolkit combining file operations (read, search, edit), terminal execution, and test running. Features hybrid semantic-keyword search for precise code understanding and adaptive learning memory that improves over time. Streamline coding, debugging, and testing workflows with reliable, memory-enhanced tools. preface critique assumes develop quality approximation conjecture ropessed development planning municipality introduction points preface producing ten considerable regarding orchestras stability partial bibliography headlining portland coordinator method whose reaction argued
Boost development efficiency with AI Dev Runtime, a comprehensive toolkit combining file operations (read, search, edit), terminal execution, and test running.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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: 3. 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") - note
frontmatter-keyunknown frontmatter key "command-tool" - note
frontmatter-keyunknown frontmatter key "command-dispatch"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (ai-dev-runtime) differs from the folder (super-ai-dev-runtime)
- 100Tools and files. No external tools needed
- 100Steps. 5 steps
- 100Execution cost. Instruction body is 236 tokens
- 100Running it twice. No mutating operations
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)
- +4Structure: 0 headings, hard to scan
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 651: enough signal without eating the budget
- +3Step-by-step instructions: 5 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.