Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add deciqAI/knowledge-skills --skill disruptive-innovationgit clone --depth 1 https://github.com/deciqAI/knowledge-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/deciqai/knowledge-skills/disruptive-innovation)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/disruptive-innovation"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/disruptive-innovation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/disruptive-innovation"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/disruptive-innovation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00138 | $0.02203 |
| Opus 5 | $0.00069 | $0.01102 |
| Sonnet 5 | $0.00028 | $0.00441 |
| Haiku 4.5 | $0.00014 | $0.00220 |
Grade A, and why
disruptive-innovation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Disruptive Innovation
Overview
Most incumbents fail not because they make bad decisions, but because they make good ones. Clayton Christensen found that leading firms listened to their best customers, invested in high-margin segments, and were displaced anyway. The pattern: incumbents overshoot mainstream customer needs, creating a price window at the low end that a new entrant can enter profitably — and the incumbent cannot match without cannibalizing its own margins. Disruptors enter there, accumulate resources, and migrate upward.
Two paths exist: low-end disruption targets price-sensitive existing customers who are over-served; new-market disruption creates consumption among people who couldn't previously participate at all.
Compose with neighbors: s-curve-technology-adoption to assess incumbent vulnerability; pmf-crossing-the-chasm after identifying the entry point; blue-ocean-strategy when the attacker wants to reshape value dimensions; second-curve for the incumbent's response problem.
When to Use
Apply when: founder choosing market entry to avoid head-to-head; incumbent assessing low-price entrant threat; investor evaluating startup structural advantage; product team defining what to deliberately exclude from MVP; someone asks whether AI agents / usage-based (per-outcome) pricing are disrupting seat-based SaaS incumbents or just a feature they'll absorb.
When NOT to use: market requires absolute performance / no "good enough" threshold (aircraft engines, Class III devices); purely a price war with no cost-structure asymmetry; someone labeling every new entrant "disruptive" (Uber is sustaining innovation); insufficient data to assess overshooting.
Coaching Novices (Adaptive Front Door)
- Engine mode: user has a specific market, incumbent, and entry point → run The Process directly.
- Coach mode: user asks "what is this / does it apply to me?" → guide step by step.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 120 lines · 138 tokens per session scan A d06155ec1232
disruptive-innovation is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 9d ago), licensed MIT. It adds 138 tokens to every session and 2,203 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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