AF s-curve-technology-adoption
Activate when: user asks "why has our growth stalled after early success?", "when will this market saturate?", "we used to grow easily, now it's hard", "how do we cross the chasm?", "we need to reach mainstream buyers", "our marketing stopped working", "what adopter stage are we in?", or mentions S-curve, diffusion of innovations, Rogers, early adopters, majority, laggards, Bass diffusion model, or technology adoption lifecycle. Do NOT activate when: the market is already mature/saturated with no diffusion dynamics left to analyze; or adoption is driven by regulatory mandate rather than buyer choice. More: deciqai.com/c/s-curve-technology-adoption
Activate when: user asks "why has our growth stalled after early success?", "when will this market saturate?", "we used to grow easily, now it's hard", "how…
As a process F 41/100 · Will not run — References files that are not bundled: examples/ryan-gross-iowa-hybrid-corn-study-1943-and-rogers-synthesis-1962.md, examples/sailing-ships-vs-steamships-technology-substitution.md, examples/generative-ai-adoption-s-curve-2022-2026.md
How to improve
- The text references files that are not there: add them or drop the references.
- 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
- warning
missing-refreference to a missing file: examples/ryan-gross-iowa-hybrid-corn-study-1943-and-rogers-synthesis-1962.md - warning
missing-refreference to a missing file: examples/sailing-ships-vs-steamships-technology-substitution.md - warning
missing-refreference to a missing file: examples/generative-ai-adoption-s-curve-2022-2026.md - warning
missing-refreference to a missing file: references/sources.md
Process rating: all ten parameters 41/100
- 0Tools and files. 4 referenced file(s) missing: examples/ryan-gross-iowa-hybrid-corn-study-1943-and-rogers-synthesis-1962.md, examples/sailing-ships-vs-steamships-technology-substitution.md, examples/generative-ai-adoption-s-curve-2022-2026.md
- 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. 2 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2657 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
- +4Description does not say when NOT to use the skill (false activations)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +3Description length 655: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 32 items
- +3Output format is stated explicitly
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.