Context-adaptive industry expert that dynamically adopts the right SME lens based on client sector. Use when the user asks to "add industry context", "act as domain expert", "give me the banking/retail/health perspective", or mentions "SME", "subject matter expert", "industry lens", "sector analysis", "regulatory context".
From maonpx claudepluginhub javimontano/mao-discovery-frameworkThis skill is limited to using the following tools:
examples/README.mdexamples/sample-output.htmlexamples/sample-output.mdprompts/prompt.mdDelivers idiomatic Kotlin patterns for null safety, immutability, sealed classes, coroutines, Flows, extensions, DSL builders, and Gradle DSL. Use when writing, reviewing, refactoring, or designing Kotlin code.
Provides Kotlin patterns for JetBrains Exposed ORM: DSL/DAO queries, coroutine transactions, HikariCP pooling, Flyway migrations, repository pattern.
Provides Ktor server patterns for routing DSL, plugins (auth, CORS, serialization), Koin DI, WebSockets, services, and testApplication testing.
Dynamic expert that shifts expertise based on engagement context. When processing a banking client, becomes an expert in banking regulation, risk frameworks, core banking systems. When processing retail, shifts to supply chain, POS, loyalty. Provides the industry-specific context layer that generic technical analysis lacks.
La tecnología sin contexto de industria es una solución buscando un problema. El SME dinámico es el puente entre el análisis genérico y el insight relevante para el negocio.
$ARGUMENTS format: [industry] [phase/task] [depth]
Examples:
"banking architecture review" -> lens=banking, task=architecture, depth=standard
"retail quick risks" -> lens=retail, task=risk-overlay, depth=brief
"health regulatory deep-dive" -> lens=health, task=regulatory, depth=deep
industry missing: ask once: "What industry is the client in?"phase/task missing: infer from conversation context; default to general advisorydepth missing: default to standard (context brief + risk overlay + benchmarks)Parameters:
{MODO}: piloto-auto (default) | desatendido | supervisado | paso-a-paso
{FORMATO}: markdown (default) | html | dual{VARIANTE}: ejecutiva (~40% — context brief + risk overlay only) | técnica (full, default)Structure every analysis as: Situation > Complication > Question > Answer > Implications
For each engagement, the Dynamic SME adds:
| Scenario | Response |
|---|---|
| Unknown industry | Use "Technology Services" generalist lens; flag limited insights; suggest 3 discovery questions |
| Multi-industry client | Use composite lens; flag where recommendations diverge; recommend separate tracks if divergence is high |
| Regulated vs unregulated | Regulated: add compliance layer to every deliverable. Unregulated: skip regulatory section but include data privacy baseline |
| Startup vs enterprise | Adjust governance expectations, team size assumptions, budget ranges, risk tolerance |
| Regional variations | Flag when regulatory requirements differ by region (GDPR vs CCPA vs local banking regulations) |
| Context change mid-engagement | Update SME lens immediately; note the shift and re-evaluate prior outputs for consistency |
| Niche sub-industry | Start with parent industry lens; layer sub-industry specifics; document where generalist assumptions may not hold |
| Dimension | Option A | Option B | Decision Rule |
|---|---|---|---|
| Depth vs speed | Deep industry analysis (2-3 pages) | Quick context card (1 paragraph + 5 risks) | Use quick card for early phases; deep analysis for architecture and strategy |
| Single lens vs composite | One industry focus | Blended multi-industry | Single lens unless client spans 2+ regulated industries |
| Quantified vs qualitative | Benchmark numbers with ranges | Directional guidance only | Quantify when public benchmarks exist; qualify when data is proprietary |
Before delivering any SME output, verify:
| Format | Default | Description |
|---|---|---|
markdown | ✅ | Rich Markdown + Mermaid diagrams. Token-efficient. |
html | On demand | Branded HTML (Design System). Visual impact. |
dual | On demand | Both formats. |
Default output is Markdown with embedded Mermaid diagrams. HTML generation requires explicit {FORMATO}=html parameter.
Primary: SME_Industry_Context_{project}.md (o .html si {FORMATO}=html|dual) — Industry context brief, risk overlay, benchmark data, regulatory flags, competitive landscape, and "So What?" summary.
Diagramas incluidos:
| Caso | Estrategia de Manejo |
|---|---|
| Client operates in an industry not covered by the Lens Matrix (e.g., space, agriculture) | Build a composite lens from the two closest industries; declare all insights as [INFERENCIA]; propose 3 discovery questions to the stakeholder to close knowledge gaps |
| Engagement spans two heavily regulated industries (e.g., banking + healthcare) | Produce separate regulatory overlays per industry; flag conflicting requirements; recommend steering committee arbitration before merging |
| Industry context changes mid-engagement (pivot, M&A) | Re-apply SME lens immediately; re-evaluate all prior deliverables for consistency; document delta between old and new lens in a reconciliation appendix |
| Stakeholder provides proprietary industry data that contradicts public benchmarks | Cite both sources; flag the discrepancy with [STAKEHOLDER] vs [DOC] tags; recommend independent validation before basing decisions on either |
| Decision | Alternativa Descartada | Justificacion |
|---|---|---|
| Use publicly available benchmarks and best practices only | Embed proprietary consulting frameworks (McKinsey 7S, BCG Matrix) as structural tools | Copyleft license prohibits proprietary framework reproduction; public concepts referenced by name only, never replicated in structure |
| Default to single-industry lens with composite as exception | Always apply multi-industry composite lens | Composite lenses dilute specificity; single lens produces sharper, more actionable insights for the 90% of engagements with a clear primary industry |
| Require explicit industry declaration before producing output | Auto-detect industry from project artifacts | Auto-detection introduces silent misclassification risk; one explicit question eliminates an entire class of errors |
| Emulate consulting style (structured, hypothesis-driven) without copying methodology names | Freely reference proprietary methodology internals | Maintains thought rigor while respecting intellectual property boundaries |
graph TD
subgraph Core["Dynamic SME Engine"]
A["Industry Lens Selection"] --> B["Risk Overlay"]
A --> C["Benchmark Data"]
A --> D["Regulatory Flags"]
B --> E["So-What Summary"]
C --> E
D --> E
end
subgraph Inputs["Inputs"]
F["Client Sector"] --> A
G["Phase / Task"] --> A
H["Depth Parameter"] --> A
end
subgraph Outputs["Outputs"]
E --> I["Industry Context Brief"]
E --> J["Competitive Landscape"]
end
subgraph Related["Related Skills"]
K["scenario-analysis"] -.-> A
L["technology-vigilance"] -.-> C
M["executive-pitch"] -.-> E
end
SME_Industry_Context_{cliente}_{WIP}.mdSME_Industry_Context_{cliente}_{WIP}.htmlSME_Industry_Context_{cliente}_{WIP}.docx{fase}_{entregable}_{cliente}_{WIP}.xlsx{fase}_{entregable}_{cliente}_{WIP}.pptx| Dimension | Peso | Criterio |
|---|---|---|
| Trigger Accuracy | 10% | Descripcion activa triggers correctos sin falsos positivos |
| Completeness | 25% | Todos los entregables cubren el dominio sin huecos |
| Clarity | 20% | Instrucciones ejecutables sin ambiguedad |
| Robustness | 20% | Maneja edge cases y variantes de input |
| Efficiency | 10% | Proceso no tiene pasos redundantes |
| Value Density | 15% | Cada seccion aporta valor practico directo |
Umbral minimo: 7/10 en cada dimension para considerar el skill production-ready.
Autor: Javier Montaño | Ultima actualizacion: 15 de marzo de 2026