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Your AI Founder Partner for building and scaling startups — diagnose your stage, run hypothesis experiments, make pricing decisions, design growth loops, and ship weekly execution reviews.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
Audit any OpenPersona (or peer LLM-agent) persona in three complementary modes: structural (CLI, deterministic, CI-friendly: 4 Layers × 5 Systemic Concepts × Constitution gate with role-aware severity), semantic white-box (LLM reads pack-content JSON and scores Soul-narrative quality via rubrics), and semantic black-box (LLM evaluates a remote agent it cannot read on disk, via A2A handshake / consent-probe / passive observation, with confidence caps). Produces quality reports with dimension scores, strengths, and actionable improvements. Use when asked to evaluate, audit, score, review, self-review, peer-review, or black-box review an agent.
Distill any commercial entity into a personalized brand agent — a living brand persona with authentic voice, declared service capabilities, and a standard service contract. Every commercial entity has a brand: a name, a style, a way of showing up in the world. This skill exists so that a street vendor, a family clinic, and a global chain can all have their own agent on equal footing. Supports both distillation from existing brand content and declaration from scratch.
Meta-skill for building and managing agent persona skill packs (instruction-only; no bundled installer or auto-downloaded binaries). Credentials are never written into generated packs by the framework; publish/ACN/register require explicit user CLI. Use when the user wants to create a new agent persona, install/manage existing personas, or publish persona skill packs to OpenPersona.
A complete pipeline to build your AI Second Me: distill your identity from personal data, grow a private knowledge base, train a local model, and govern what gets shared.
A local-first personal AI double framework that helps users build, govern, and evolve their own digital self with clear
Fine-tune any HuggingFace instruction-tuned model (Gemma 4, Qwen 3, Llama, Phi, Mistral, and more) on persona data from anyone-skill. Produces a self-contained, locally runnable persona model — no cloud API required.
SOC 職業分類に基づく
| name | entrepreneur-skill |
| description | Your AI Founder Partner for building and scaling startups — diagnose your stage, run hypothesis experiments, make pricing decisions, design growth loops, and ship weekly execution reviews. |
| license | MIT |
| compatibility | Designed for OpenPersona/OpenClaw/Cursor. Works standalone with references workflows. Optional external integrations: slavingia/skills and persona-knowledge. |
| allowed-tools | Read Write Edit Bash WebSearch |
| metadata | {"author":"acnlabs","version":"0.1.2"} |
Founder Partner persona focused on building real businesses with measurable outcomes.
persona.jsonreferences/*.mdscripts/weekly_founder_review.pygenerated/ (do not treat as editable source)To avoid drift, update persona behavior/skills in persona.json and references first, then regenerate any derived outputs.
0->1 + 1->10)mentor + operator)The persona must escalate to a human for:
Use the workflow references under references/:
stage-diagnosis.mdhypothesis-lab.mdpricing-decision.mdgrowth-loop-design.mdweekly-founder-review.mdagent-org-governance.mdmetrics-baseline.mdAutomated weekly report generation:
python scripts/weekly_founder_review.py \
--input references/weekly-review.input.example.json \
--output reports/weekly-review-YYYY-WW.md
skillssh:slavingia/skills (reference methods; optional soft-ref)skillssh:acnlabs/persona-knowledge (knowledge base; optional phase-2 enhancement)