Sponsored by

Find leads on Reddit on auto pilot

Topic: opencode

1,723 skills in this topic.

compose-team Assemble the context bundles for each sub-agent based on evaluate-story output. Produces spawn-ready packages for Planning, Implementation, QA, or MicroDelivery sub-agents. Activate after evaluate-story, before spawning any sub-agent.
Fr-e-d/GAAI-framework 123
coordinate-handoffs Validate sub-agent handoff artefacts, sequence phase transitions, and manage retry and escalation logic. Activate after each sub-agent terminates to determine next action.
Fr-e-d/GAAI-framework 123
delivery-high-level-plan Transform validated Stories into a clear, minimal, governed execution plan. Used by the Planning Sub-Agent as the first planning pass before prepare-execution-plan for Tier 2/3, or as the sole planning output for simple Stories.
Fr-e-d/GAAI-framework 123
evaluate-story Assess Story complexity, identify required domains, and determine delivery tier (MicroDelivery / Core Team / Core Team + Specialists). Activate as the first step of every delivery orchestration cycle.
Fr-e-d/GAAI-framework 123
implement Generate correct, minimal, maintainable code that satisfies a validated Story's acceptance criteria against an execution plan. Activate when a Story is validated, a plan exists, and all prerequisites are unambiguous.
Fr-e-d/GAAI-framework 123
prepare-execution-plan Decompose a high-level delivery plan into a precise, file-level execution sequence with explicit ordering, edge cases, and test checkpoints. Activate after delivery-high-level-plan for complex or multi-phase Stories before implementation begins.
Fr-e-d/GAAI-framework 123
qa-review Validate that implemented code fully satisfies Story acceptance criteria, respects rules, and introduces no regressions. This is the hard quality gate — no pass means no delivery. Activate after implementation is complete.
Fr-e-d/GAAI-framework 123
remediate-failures Correct failures, rule violations, and acceptance criteria gaps detected during QA review. Activate when qa-review returns FAIL. Fixes without redefining scope — loops until all quality gates pass.
Fr-e-d/GAAI-framework 123
create-prd Produce a lightweight strategic PRD that defines product vision, user problem, value hypothesis, success metrics, and scope boundaries. Activate only when starting a new product, launching a major initiative, or facing strategic uncertainty.
Fr-e-d/GAAI-framework 123
discovery-high-level-plan Transform vague or high-level human intent into a governed Discovery action plan. Activate when intent is unclear, broad, or when multiple discovery steps are required before any artefact is created.
Fr-e-d/GAAI-framework 123
generate-epics Translate product intent or a PRD into a small set of outcome-driven Epics (3–7 max). Activate when starting a new product, adding a significant feature domain, or breaking down a PRD into actionable user outcomes.
Fr-e-d/GAAI-framework 123
generate-stories Translate a single Epic into clear, actionable User Stories with explicit acceptance criteria. Activate when an Epic is defined and work needs to be prepared for Delivery execution.
Fr-e-d/GAAI-framework 123
refine-scope Iteratively refine Discovery artefacts (plans, epics, stories) when feedback, ambiguity, or uncertainty is detected. Activate when artefacts are incomplete, acceptance criteria are missing, or human feedback highlights gaps.
Fr-e-d/GAAI-framework 123
review-story-alignment Adversarial review of generated stories against the Discovery Session Brief, referenced DECs, and Epic DoR. Detects contradictions, omissions, and intent drift BEFORE stories reach Delivery. Produces a structured verdict (PASS/FAIL) with specific findings per story. Triggers after generate-stories, before backlog registration as refined.
Fr-e-d/GAAI-framework 123
validate-artefacts Validate that all Discovery artefacts (Epics, Stories) are clear, governed, complete, and safe to pass into Delivery. Activate after generating Epics or Stories and before any Delivery planning. This is the mandatory Discovery → Delivery gate.
Fr-e-d/GAAI-framework 123
AgentDB Vector Search Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
spencermarx/open-code-review 126
browser Web browser automation with AI-optimized snapshots for claude-flow agents
spencermarx/open-code-review 126
github-code-review Comprehensive GitHub code review with AI-powered swarm coordination
spencermarx/open-code-review 126
Pair Programming AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
spencermarx/open-code-review 126
ReasoningBank with AgentDB Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
spencermarx/open-code-review 126
ReasoningBank Intelligence Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
spencermarx/open-code-review 126
V3 CLI Modernization CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation.
spencermarx/open-code-review 126
V3 Core Implementation Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.
spencermarx/open-code-review 126
V3 Swarm Coordination 15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
spencermarx/open-code-review 126