Total Skills
9
Skills published by Innorve-Inc with real stars/downloads and source-aware metadata.
Total Skills
9
Total Stars
0
Total Downloads
0
Comparison chart based on real stars and downloads signals from source data.
innorve-capability-graph
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innorve-evidence-binder
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innorve-maturity-gate
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innorve-method
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innorve-multi-tool
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innorve-policy-as-code
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innorve-skill-architecture
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innorve-skill-contract
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Use when a team or organization is starting to introduce AI into delivery work and needs an honest map of which SDLC phases have AI today, which don't, where humans must stay in the loop, and where the real capability gaps are. Coaches the user to produce a Capability Graph (Mermaid) and a Capability Map (text) covering all seven phases — Discover, Define, Build, Verify, Release, Operate, Learn.
Use when starting an AI system that will eventually face an audit, customer security review, or regulator. Scaffolds a Governance Binder — a folder layout and template set that the team fills in as they build, so evidence accumulates in lockstep with code rather than being reconstructed under deadline pressure.
Use when deciding whether an AI skill or agent is ready to graduate from one level to the next on the Skill Maturity Ladder (Incubating → Validated → Certified → Deprecated). Walks the user through gate criteria, produces a Maturity Gate Report that documents the decision, and lists specific actions to close any gaps.
Use when the user asks about the Innorve Method, asks "where do I start" with AI-native architecture, references IM-01 through IM-08, mentions the Innorve Architect Ladder, or wants to know which Innorve skill to invoke for their current situation. This is the meta index — invoke it first when the path forward is unclear.
Use when picking the model + framework + deployment combination for a specific AI skill, and the choice needs to survive vendor pricing changes, term changes, model deprecations, and shifting latency/cost trade-offs over the next 18-36 months. Coaches the user through skill type, latency, cost, regulatory environment, and existing stack, then produces a Multi-Tool Decision document with explicit fallbacks and migration triggers per choice.
Use when the user has a governance rule, compliance requirement, regulatory constraint, or internal policy expressed in prose and needs to make it machine-enforceable. Coaches the engineer through translating natural-language rules into version-controlled policy code with explicit applicability, enforcement, and audit hooks. Invoke when a system has skills (IM-01) but governance still lives in PDFs, wikis, or "we just know."
Use when the user is starting a new AI-native system, has a working prototype that is one undifferentiated blob, asks how to decompose an agent into reusable parts, or asks for a "skill graph". Coaches the engineer through breaking the work into named, testable, composable skills and producing a Skill Graph artifact. Invoke as the first step in the Innorve Method when the team is at L0 or L1.
Use when authoring a new AI skill or agent capability that will be called by other systems, exposed to users, or shipped to production. Walks the author through a structured wizard and emits a Skill Contract — a machine-readable file conforming to the Innorve Skill Contract Schema v0.1 that declares inputs, outputs, evidence, side effects, risk class, approvals, and eval criteria.
Use when designing or operating an AI system and the right architectural posture is unclear — startup (lightweight), enterprise (formal controls), or regulated (strict approvals + immutable evidence). Coaches the user through environment, data classification, approval flow, and audit requirements, then produces a Tenant Posture Card that documents which posture applies and what it requires.