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av/harbor

Skill Claude CodeCodex

Use when the user requests integration testing, feature validation, or test plan execution.

av/harbor

Skill Claude CodeCodex

Use when the user wants to systematically fix AI code slop — duplicated logic, over-engineering, silent error swallowing, convention drift, cargo-cult patterns, and other LLM-introduced architectural decay — over a specified duration.

av/harbor

Skill Claude CodeCodex

Systematically explore and test any software project (CLI, API, Backend, Library, etc.) to find bugs, usability issues, and edge cases. Produces a structured report with full reproduction evidence (exact commands, inputs, logs, and tracebacks) for every issue.

av/harbor

Skill Claude CodeCodex

Fully autonomous bug hunting pipeline — discover bugs in a scoped area using parallel subagents, independently triage each finding, fix confirmed issues with subagents, then audit all fixes against repo constraints and target platforms. Runs end-to-end without user interaction.

av/harbor

Skill Claude CodeCodex

Bulletproof agent operating protocol. 15 failure-prevention rules distilled from 120+ real sessions and 10 agent definitions. Covers fabrication, constraint tracking, verification, scoping, retry discipline, and communication. Load before any task to prevent the most common agent failure modes.

av/harbor

Skill Claude CodeCodex

Scan the codebase and classify every fact by lifecycle stage — tag @draft, @spec, or @implemented based on what the code actually shows. Add missing facts, fix inaccurate ones, remove obsolete ones. Use when asked to discover facts, bootstrap or update a fact sheet, scan the codebase for truths, sync facts to match…

av/harbor

Skill Claude CodeCodex

Operate on @spec facts — implement them in code, then tag @implemented. Use when asked to implement facts, implement the spec, build from the fact sheet, make facts true, or work through unimplemented requirements.

av/harbor

Skill Claude CodeCodex

Operate on @draft facts — collaboratively refine them into precise, actionable @spec facts. Resolve ambiguities, fill gaps, eliminate contradictions, and sharpen labels until every fact is ready to implement. Use when asked to refine facts, clarify the spec, review facts for quality, or "work on facts" with the user.

av/harbor

Skill Claude CodeCodex

Manage .facts files — atomic, validatable truth statements about a project. Install, check, list, add, edit, remove, and lint facts via the CLI. ALWAYS read this skill when the user mentions facts in any capacity.

av/harbor

Skill Claude CodeCodex

Timeboxed ideation on a topic using propose-and-critique subagent pairs. Use when the user wants to brainstorm, explore ideas, discover features, generate options, or think through possibilities for a specified duration. Triggers on requests like "brainstorm X for 30 minutes", "ideate on X", "spend an hour thinking…

av/harbor

Skill Claude CodeCodex

Create new Harbor Boost modules — the Python plugins that run inside Harbor's LLM proxy. Use this skill whenever the user wants to build a Boost module, write a custom module for Harbor Boost, add a new feature to the Boost proxy pipeline, or create any kind of middleware that transforms, augments, or intercepts LLM…

av/harbor

Skill Claude CodeCodex

Add a new service to Harbor — scaffold the compose config, environment variables, metadata, documentation, and cross-service integrations. Use this skill whenever the user wants to add a new service to Harbor, integrate a new tool/app/model server, create a compose configuration for a new project, or onboard any…

av/harbor

Skill Claude CodeCodex

Perform Harbor release procedures — version bumping, codegen, committing, pushing, and drafting GitHub releases. Use this skill when the user wants to release a new version of Harbor, bump the version number, create a release on GitHub, run the release codegen pipeline, or anything related to shipping a new Harbor…

av/harbor

Skill Claude CodeCodex

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

av/harbor

Agent Codex

Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.

av/harbor

Agent Codex

Compare two outputs WITHOUT knowing which skill produced them.

av/harbor

Agent Codex

Evaluate expectations against an execution transcript and outputs.

av/harbor

Skill Claude CodeCodex

Live-test a Harbor Boost module by sending a real prompt through llamacpp via pi and validating the output. Use when asked to test a boost module, verify a module works, check module behavior, QA a boost module, or confirm a module's effect on LLM output.

av/harbor

Skill Claude CodeCodex

Use when the user specifies a task and a duration, and the work should be done iteratively by subagents over that time period.

av/harbor

Hook Claude Code

Runs before the agent uses a tool for Bash tool calls, running an inline shell check. From av/harbor.

av/harbor

Settings file Claude Code

Agent settings declaring 1 hook event (PreToolUse).

av/harbor

Instructions file CodexOpenCode

Instructions for av/harbor, covering harbor project, key locations, cli reference, adding a new service and config & profiles.

av/harbor

Instructions file

Instructions for av/harbor, a project described as: Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore.

av/harbor

Skill Claude CodeCodex

Skill "boost-modules" from av/harbor, covering harbor boost custom modules, module structure, quick reference, output methods and stream text to client.