AC error-message-improver
Help users with Validated demand: Users and support teams need clearer error messages that explain what failed, why it failed, and what action to take next. This requirement is supported by 12 separate online signals across 3 source families, so it represents broader demand rather than a single isolated request.. Use when a user asks for work-productivity, error messages, debugging, user feedback, support, or needs a practical workflow, artifact, checklist, analysis, or implementation support for this requirement.
Help users with Validated demand: Users and support teams need clearer error messages that explain what failed, why it failed, and what action to take next.
As a process C 64/100 · Has gaps — weak spots: result and completion, when it triggers, consistency
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: 0. 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 64/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (error-message-improver) differs from the folder (error-message-improver-014620)
- 50Failures and branches. 0 branches, has a failure section
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 16 steps
- 100Execution cost. Instruction body is 632 tokens
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 519: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 16 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.