weebcoder101

DEEP multi-step research harness. Decomposes queries into sub-questions, executes parallel web searches via Pieces MCP, iteratively refines with gap detection, and synthesizes cited reports. Architecture inspired by GPT Researcher (27.6k stars), Vane/Perplexica (35.2k stars), and Gemini Deep Research. Use when user asks for deep research, investigation, analysis, comparison, or any task requiring exhaustive web research.

DEFAULT THINKING MODE — not a feature, but how the agent operates. Every task gets innovation-overdrive thinking: research, ground, reflect on contradictions, propose, then build. This is the agent's identity, not a command. Integrates MiMo-Code's 6-phase memory consolidation.

Chain execution manager: validates dependencies, enforces order, tracks violations. Use to verify that all required skill chains were executed and to get the correct execution order.

API design patterns, REST conventions, and endpoint standards. Use when creating or modifying API endpoints. Covers routing, request/response patterns, error handling, and versioning.

Architectural design, system patterns, and dependency management. Use when designing new modules, refactoring existing systems, or making architectural decisions. Covers layering, coupling, cohesion, and design patterns.

Trigger-driven automation definitions and runner management. Use when creating, running, or managing skill-based automation pipelines.

DEFAULT THINKING MODE — not a feature, but how the agent operates. Every task gets innovation-overdrive thinking: research, ground, reflect on contradictions, propose, then build. This is the agent's identity, not a command. Integrates MiMo-Code's 6-phase memory consolidation.

Customize opencode configuration, theme, keybindings, and agent settings. Use when modifying dreamcode/opencode behavior, adding custom agents, or adjusting system preferences.

META-SKILL — mandatory entry point for EVERY non-trivial prompt. Decomposes prompt into 5 orthogonal cursors (Temporal, Source, Gesture, Topic, People), fires parallel Pieces LTM searches with pagination until confidence >= threshold, then orchestrates the full neuro (10 iter) -> code-hardener (5 iter) -> implementation -> lint-fixer (5 loop) chain. Self-evolutionary: after every run, analyzes outcomes and updates its own structure. Integrates, wraps, and supersedes neuro, code-hardener, and lint-fixer.

Mandatory external architectural and code-review harness for ANY non-trivial task including code changes, bug fixes, new features, refactors, API changes, data contract changes, performance optimizations, security fixes, architectural decisions, configuration changes, test modifications, integration work, debugging, analysis, planning, and implementation. Use when the user requests any modification, analysis, debugging, testing, integration, or planning work. Use for EVERY prompt that involves understanding or changing code, data, or configuration. When in doubt, ALWAYS use this skill. Skip only for trivial changes: typo fixes, formatting-only changes, one-line lint fixes, comment cleanup, simple unused import removal.

Mandatory second-stage logic filter and architectural hardening skill that runs after NEURO for ANY code change, bug fix, new feature, refactor, API change, data contract change, performance optimization, security fix, architectural decision, configuration change, test modification, integration work, debugging, analysis, planning, or implementation. Executes exactly 5 mandatory iterations. Validates NEURO recommendations against repo truth, calls NEURO with filtered critique, then emits the only implementation plan opencode may follow. Use after any neuro skill usage. Use when code is about to be edited. Use for every non-trivial code modification.

Mandatory post-implementation lint and type-checking skill that runs after ANY code change, bug fix, new feature, refactor, API change, or configuration modification. Ensures all ruff lint errors, mypy type errors, and ESLint issues are resolved. Use after every implementation that modifies source files. Use when code has been edited. Use for every response where file edits were made.

Mandatory second-stage logic filter and architectural hardening skill that runs after NEURO. It validates NEURO recommendations against repo truth, calls NEURO a second time with filtered critique, then emits the only implementation plan Gemini may follow.

Mandatory external architectural and code-review harness for non-trivial code changes, PR reviews, refactors, modeling logic, dashboard/API integration, performance-sensitive work, and implementation planning. Must be followed by the code-hardener skill before Gemini edits production code.