Semantic vector search with moflo — RAG over your own documents, similarity matching, context-aware retrieval via HNSW (node:sqlite-backed). Use when building retrieval layers for chat, search, or context-assembly.
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Semantic vector search with moflo — RAG over your own documents, similarity matching, context-aware retrieval via HNSW (node:sqlite-backed). Use when building retrieval layers for chat, search, or context-assembly.
日本語の概要は準備中です。原文の説明を表示しています。
Tune moflo's memory stack for speed, RAM, and index quality. Covers HNSW parameters (M, efConstruction, ef), vector quantization, batch operations, and common bottlenecks. Use when scaling past ~100k entries or when search latency regresses.
日本語の概要は準備中です。原文の説明を表示しています。
Persistent memory patterns for moflo agents — session memory, long-term knowledge, pattern learning, and cross-session context via moflo's node:sqlite + HNSW vector store. Use when building stateful agents or assistants that need to remember across runs.
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Generate and maintain the project's TECHNICAL documentation from its codebase — scans the project structure, tech stack, and module boundaries, then writes a lean README landing page plus detailed topic pages (architecture, modules, setup, build, APIs), only the docs that are relevant. Use whenever the user wants to create, update, or validate documentation of the CODE or the project itself, e.g. "generate documentation", "create docs", "write the README", "update the project docs", "document the codebase", "document this project's architecture", "validate the project documentation". This is CODE / project documentation only — it never documents the game design. To render the GAME DESIGN (the GDD: systems, flows, content, economy) for people to read use /unikit-gd-docs.
日本語の概要は準備中です。原文の説明を表示しています。
Mechanical consistency check for game design — answers "is the design consistent with itself?" — plus changed-scope impact analysis across all three GDD axes: systems, flows, and content types. Offline and deterministic: greps the facts registry against the documents (numbers, terms, IDs, duplicate & dangling references, roster↔disk, map freshness, Depends 3-way, status/version, AC presence, placeholder leaks, flow & content schema), and from a git diff computes which dependent systems, flows, and content a change affects. Scope is inferred: a named document checks that document; an unverified diff triggers a changed-scope pass; otherwise everything. Use when the user wants a consistency or impact check, e.g. "verify the design", "what did this change affect", "find broken references in the design". Conflicts triage into four tracks; the entailed fixes hand off to /unikit-gd-apply in one pass. This is the mechanical pass — for a subjective "is this design good" quality critique use /unikit-gd-review.
日本語の概要は準備中です。原文の説明を表示しています。
Research and ideation partner for GAME DESIGN — think through design ideas before writing them into the GDD; produces a brief, never edits the GDD itself. Use to assess a genre or market for viability, dissect a reference game (mechanics → dynamics → aesthetics), explore how to improve or extend an existing system, flow, or content type, research new mechanics the design lacks, investigate a part of the GDD in code, or develop the research bucket of a /unikit-gd-review report into decided edits. Trigger on "explore how to improve the flow", "ways to improve the combat system", "is this genre saturated", "break down the combat of Hades", "work out the review's open questions". GAME-DESIGN research only — for CODE or technical research use /unikit-explore; to reconstruct a design from code use /unikit-gd-recon; to write a change into the GDD use /unikit-gd-system or /unikit-gd-spec; to apply edits you know use /unikit-gd-apply; to invent a new game use /unikit-gd-brainstorm.
日本語の概要は準備中です。原文の説明を表示しています。
Navigator and help guide for the UniKit framework — use when the user is unsure what to do next, where to start, or which unikit skill fits their situation. It diagnoses intent and points to the right skill or pipeline: starting a project, writing code, testing, planning, the spec-driven code workflow, authoring or detailing game design, finding a new mechanic, or deciding what game to build. Trigger on questions like "what do I do next", "where do I start", "how do I start coding", "how do I test my code", "how do I create the game design", "how do I detail a system", "how do I find a new mechanic", "which unikit skill should I use", "how does the code pipeline relate to game design", "I'm lost in unikit", "help me with unikit". Read-only — it explains and points to the right command, it never edits project files. For technical code research use /unikit-explore; for game-design research use /unikit-gd-explore; to initialize the framework use /unikit.
日本語の概要は準備中です。原文の説明を表示しています。
Prospective failure imagination for a plan, decision, or running system. Operates in two modes — **plan mode** (a plan has not yet been committed to; imagine its catastrophic failure broadly) and **scenario mode** (a specific catastrophic scenario is posed against an existing system; investigate causes against the actual code and architecture). Spawns parallel pre-mortemers in isolation across three categories of lens: standard failure classes (technical, operational, estimation, scope, adoption, dependency, team, incentive, detection, reversibility, adversarial), 0-3 ad-hoc target-specific lenses the orchestrator names when warranted, and a first-principles lens that always runs to catch what the prescribed taxonomy misses. Synthesizes into a prioritized risk register with early-warning signals. Produces feedback only — no code, no tickets, no artifacts.
日本語の概要は準備中です。原文の説明を表示しています。
Mechanical documentation hygiene. Spawns a doc-maintainer agent to audit all project documentation and fix correctness, completeness, freshness, and consistency issues autonomously within its authority. Surfaces anything requiring user judgment for approval.
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Analysis of Competing Hypotheses. Operationalizes Richards Heuer's CIA-tradition technique for systematically narrowing among multiple hypotheses against evidence. Builds an explicit hypothesis-vs-evidence matrix and focuses on disconfirmation rather than confirmation — the central insight: hypotheses cannot be proven, only disconfirmed; the surviving hypothesis is the one with the least disconfirming evidence. Spawns parallel hypothesizers (in isolation, across hypothesis-generation angles) and parallel evidence-gatherers (across evidence classes), then synthesizes into a matrix, diagnosticity analysis, sensitivity analysis, and falsification milestones. Produces feedback only — no code, no tickets, no artifacts.
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Autonomous technical lead. Takes commander's intent and drives a project to completion through an OODA loop over implementation, refactoring, review, and bug-hunting skills. Has broad authority — creates tickets, commits, invokes any skill — and only escalates via andon cord for irreversible actions, public releases, or genuinely blocking decisions. User acts as product owner; skill acts as tech lead.
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Proactive bug-hunting workflow. Assesses codebase risk through complexity, coverage, and structural analysis, then spawns focused investigators that write reproducing tests to validate suspected bugs. Thoroughness over speed. Advisory only — produces findings and proposes tickets; does not implement fixes.
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Abductive reasoning about causes. Takes a phenomenon, separates observations from interpretations, then spawns diagnosticians applying different reasoning lenses (technical, human-factors, process, incentive-structure, environmental, temporal, measurement-artifact, statistical) in isolation. Orchestrator evaluates candidate causes for fit-against-evidence, calibrates confidence honestly, and reports leading candidate(s) with distinguishing evidence needed. Produces feedback only — no code, no tickets, no artifacts.
日本語の概要は準備中です。原文の説明を表示しています。
Good-faith divergent brainstorming for achieving a goal. Validates assumptions, then spawns brainstormers running different techniques (first-principles, working-backwards, lateral, analogical, constraints-shift, etc.) in isolation, and synthesizes the pool into a report of standouts, reasonable ideas, and hybrid combinations. Produces feedback only — no code, no tickets, no artifacts.
日本語の概要は準備中です。原文の説明を表示しています。
One-command setup for cqs in a new project — skills, tears infrastructure, CLAUDE.md, init, index.
日本語の概要は準備中です。原文の説明を表示しています。
The idle work loop - enumerate open issues and triage rows, classify fixable vs blocked, pick by value-vs-budget, dispatch. Standing user directive; invoke whenever otherwise idle.
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Rebuild the cqs index and show before/after stats comparison.
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Run before starting an implementation task — scout + gather assemble relevant files, functions, tests, and notes into a brief.
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Comment-archaeology sweep - find work items hiding in TODO/FIXME/for-now comments and plan-doc ledgers, judge them, file issues, queue trivial fixes. Good idle-loop activity.
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Unified cqs CLI dispatcher — semantic code search, call graph navigation, impact analysis, quality tools, notes, and infrastructure. Use `/cqs <command> [args]` for any cqs operation.
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Review project docs for staleness. Checks lib.rs, Cargo.toml, README, CONTRIBUTING, SECURITY, PRIVACY, and GitHub repo metadata.
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Task planning with scout data + task-type templates. Produces implementation checklists.
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Execute multiple cqs queries in a single persistent session via stdin batch mode.
日本語の概要は準備中です。原文の説明を表示しています。
Diagnose common cqs issues — stale index, model download, schema mismatch, connection issues.
日本語の概要は準備中です。原文の説明を表示しています。