strategic-moat SKILL.md skillA
strategic-moat from aniganti/pm-superpowers is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add aniganti/pm-superpowers/strategic-moat@git:20261017.d23dacdPins git:20261017.d23dacd in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- aniganti/pm-superpowers
- Path
plugins/pm-superpowers/skills/strategic-moat/SKILL.md- Versions recorded
- 4
- Latest version
- git:20261017.d23dacd, committed Oct 17, 2026
- First version recorded
- Mar 18, 2026
- Size
- 16,639 bytes
- Repository stars
- 48
- License
- MIT
Assess the defensibility of a product or company across 8 moat types, grounded in habit-forming product theory, the Fogg Behaviour Model, and aggregation theory. Trigger phrases: "moat analysis", "strategic moat", "defensibility assessment", "competitive moat", "how defensible is my product".
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Strategic Moat Assessment You are a strategic moat analyst. Your job is to rigorously assess the defensibility of a product or company across eight moat types, surface evidence for each, and identify concrete opportunities to deepen every moat. If the PM wants a quick first read or just installed and wants value now, use `find-your-moat` instead of this full assessment. ## Foundational Concepts Before you begin the assessment, internalize these three frameworks — they underpin the entire analysis. ### 1. Habit-Forming Products as Moats When users invest time, money, and emotion into a product, their anticipation of future benefits keeps them coming back. This creates a self-reinforcing feedback loop: investment leads to anticipation, anticipation leads to return usage, return usage leads to deeper investment. Products that achieve this loop possess one of the strongest moats available — the user's own behaviour. ### 2. Fogg Behaviour Model (B = MAP) Behaviour = Motivation x Ability x Prompt. - **Motivation** — The user's desire to act (pain/pleasure, hope/fear, social acceptance/rejection). …
Read the whole file at its exact version.
How to install
mdr add aniganti/pm-superpowers/strategic-moat@sha256:63f0828d482f3ab4The line at the top of this page pins the label git:20261017.d23dacd, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_zyatam4hktspaais)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Mar 18, 2026 and Oct 17, 2026, about one every 71 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261017.d23dacd latest | 2026-10-17 | d23dacd | 16,639 B | A | view · diff |
| git:20260918.57b9a89 | 2026-09-18 | 57b9a89 | 12,208 B | A | view · diff |
| git:20260325.b384a8a | 2026-03-25 | b384a8a | 12,079 B | A | view · diff |
| git:20260318.6de6391 | 2026-03-18 | 6de6391 | 8,452 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (16639 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
aniganti/pm-superpowers · 48 stars · license MIT · pushed 2026-10-20 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_zyatam4hktspaais GET https://markdownregistry.com/api/v1/resolve?ref=aniganti/pm-superpowers/strategic-moat GET https://markdownregistry.com/api/v1/blob/63f0828d482f3ab4e909b7de207235ad18327fda3a77e93f4144fa9f39603356
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.