n-agentic-harnesses-codex
This skill provides a structured framework for designing, evaluating, and refining agentic systems across developer tools, assistants, workflow runtimes, and AI-powered products. Use it when architecting tool-use systems, reviewing agent permissions and state management, planning implementation phases, or assessing gaps in existing harnesses for observability, durability, or user experience. The skill emphasizes lean solo-maintainable designs, explicit system boundaries, and evaluation strategies grounded in concrete success criteria rather than prompt optimization.
git clone --depth 1 https://github.com/NateBJones-Projects/OB1 /tmp/n-agentic-harnesses-codex && cp -r /tmp/n-agentic-harnesses-codex/skills/n-agentic-harnesses/variants/codex ~/.claude/skills/n-agentic-harnesses-codexSKILL.md
# N Agentic Harnesses For Codex Use this skill as a router for designing, building, and evaluating agentic harnesses. Read only the files you need. Do not load the entire reference set unless the request genuinely spans multiple subsystems. Default posture: - Bias toward lean, solo-maintainable architecture. - Start with a single-agent design unless clear constraints justify more. - Require an evaluation plan even for greenfield builds. - Prefer explicit system boundaries, permission policy, and workflow state over prompt cleverness. - Translate ideas into implementation phases, success criteria, and failure tests. ## Step 1: Classify The Request Choose one mode before reading reference files. ### `design` Use when the user is creating a new harness, planning a major rebuild, or asking for architecture, MVP, or implementation sequencing. Default reads: - `references/01-principles-and-solo-dev-defaults.md` - `references/02-harness-shapes-and-architecture.md` - `references/08-design-and-build-playbook.md` Add subsystem files only as needed. ### `evaluation` Use when the user already has a harness and wants gaps, risks, missing primitives, UX upgrades, or architectural cleanup. Default reads: - `references/01-principles-and-solo-dev-defaults.md` - `references/09-evaluation-and-improvement-playbook.md` Add subsystem files only for the parts under review. ### `design + evaluation` Use when the user wants a target architecture and a way to verify it, compare it with an existing system, or define acceptance criteria before building. Default reads: - `references/01-principles-and-solo-dev-defaults.md` - `references/02-harness-shapes-and-architecture.md` - `references/08-design-and-build-playbook.md` - `references/09-evaluation-and-improvement-playbook.md` ## Step 2: Classify The Product Shape Determine the closest product shape before going deeper: - code agent - chat assistant - workflow orchestrator - internal copilot - embedded AI product feature - hybrid system If the request is ambiguous, pick the closest shape and state the assumption. ## Step 3: Read The Smallest Useful Reference Set Read these only when the request needs them: - `references/01-principles-and-solo-dev-defaults.md` Use first for almost every request. It defines the default decision posture. - `references/02-harness-shapes-and-architecture.md` Read when choosing system shape, boundaries, lifecycle, transports, or deployment structure. - `references/03-tools-execution-and-permissions.md` Read when the request involves tool registries, tool calling, approval gates, sandboxes, or trust tiers. - `references/04-state-sessions-and-durability.md` Read when the request involves sessions, resumability, retries, idempotency, approval waits, or long-running work. - `references/05-context-memory-and-evaluation.md` Read when the request involves context windows, retrieval, memory, provenance, evals, replay tests, or regression detection. - `references/06-agents-and-extensibility.md` Read when the request involves multi-agent design, plugins, hooks, skills, or extension surfaces. - `references/07-ux-observability-and-operations.md` Read when the request involves streaming UX, health checks, logs, analytics, budgets, or supportability. - `references/08-design-and-build-playbook.md` Read when the user needs a build-ready plan from idea to implementation. - `references/09-evaluation-and-improvement-playbook.md` Read when the user needs findings, missing primitives, upgrade priorities, or acceptance tests. - `references/10-example-requests-and-output-patterns.md` Read when you need prompt examples or response structure examples. - `references/11-codex-translation-notes.md` Read only when adapting this Anthropic-style skill into a Codex-oriented version or when mapping concepts between the two environments. Do not rely on reference-to-reference chains. This file is the index. ## Operating Rules - Convert vague ambitions into concrete harness primitives. - Push back on unnecessary complexity. - Treat workflow state, permissions, context assembly, and evaluation as first-class architecture, not cleanup tasks. - Separate universal harness primitives from product-specific manifestation. - For evaluation requests, present findings first and improvement sequence second. - For design requests, include how the design will be tested before calling it done. ## Output Contract ### For `design` Return: - recommended harness shape - core primitives and subsystem boundaries - MVP boundary - phased implementation plan - verification and acceptance criteria ### For `evaluation` Return: - findings ordered by severity or leverage - missing or weak primitives - user experience and operational gaps - prioritized upgrade path - tests or checks that confirm the fixes ### For `design + evaluation` Return: - target architecture - comparison against current or likely failure modes - implementation phases - acceptance criteria - evaluation plan covering regressions, safety, and UX ## Final Check Before Responding - Did you keep the design lean enough for a solo developer unless the request clearly demanded more? - Did you avoid recommending multi-agent coordination by default? - Did you include evaluation, not just construction? - Did you give the user an operational path forward instead of abstract theory?
Continuous learning system that extracts reusable knowledge from work sessions. Triggers: (1) /aiception command, (2) 'save this as a skill' or 'extract a skill from this', (3) 'what did we learn?', (4) after non-obvious debugging or trial-and-error discovery. Creates new skills when valuable reusable knowledge is identified. Integrates with Open Brain to prevent duplicates.
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Morning digest of yesterday's Open Brain thoughts, drafted to Gmail
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