AC work-productivity-self-improving-workflow-helper
Help users with Validated demand: Agent users show strong demand for Self-Improving + Proactive Agent-style workflows on Clawhub. They need practical help fixing bugs, hardening setup and safety, improving reliability, or creating adjacent skills inspired by the same job-to-be-done. This requirement is supported by 12 separate online signals across 4 source families, so it represents broader demand rather than a single isolated request.. Use when a user asks for work-productivity, self-improving-proactive-agent, self, improving, proactive, or needs a practical workflow, artifact, checklist, analysis, or implementation support for this requirement.
Help users with Validated demand: Agent users show strong demand for Self-Improving + Proactive Agent-style workflows on Clawhub.
As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
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: 7. 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 59/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (work-productivity-self-improving-workflow-helper) differs from the folder (work-productivity-self-improving-workflow-helper-140352)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 16 steps
- 100Execution cost. Instruction body is 696 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 655: 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.