AC resource-time-compression
Activate when: user says 'this will take years', 'we need to build this from scratch', 'we don't have the resources to move faster', 'how do we compress our timeline', 'competitors are already ahead and we can't catch up sequentially', or when a goal is achievable but the default sequential plan is too slow for the market window. Do NOT activate when: the bottleneck is a genuine sequential dependency that cannot be parallelized (e.g., regulatory approval must precede launch); or when required external resources do not yet exist and the problem requires first-principles innovation rather than resource configuration. More: deciqai.com/c/resource-time-compression
Activate when: user says 'this will take years', 'we need to build this from scratch', 'we don't have the resources to move faster', 'how do we compress our…
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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: 4. 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 51/100
- 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
- 30Running it twice. 4 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 26 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2338 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 668: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 26 items
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.