Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.
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。
8,214 件 ・ 関連度順
概要と使いどころ
Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.
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。
Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.
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。
Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.
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。
Track approved container images and write back the matching GitOps manifest changes instead of hand-editing tags across Argo CD applications.
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。
Aider is an open-source AI pair programming tool that runs in your terminal, letting you collaborate with LLMs to edit code across your entire codebase. With 42k+ GitHub stars and 15 billion tokens processed weekly, it features deep git integration, repo-wide code mapping, and support for 100+ programming languages.
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。
Automatically optimize AI agent credit usage by routing tasks to the most cost-efficient execution path. Use when you want to reduce AI API costs by 30-75% without quality loss, classify task complexity before execution, route simple tasks to free or low-cost models, split complex tasks into optimized sub-tasks, or detect vague prompts before wasting credits.
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。
Decompose dense codebase-wide, multi-document, PDF, and aggregation work even when the input fits the context window, following Recursive Language Models (Zhang, Kraska, Khattab, 2025). Use when the user asks to analyse all files, a whole repo, all docs, large PDFs, or to aggregate or multi-hop across scattered sources. Skip one file, one function, a single needle, or a one-page PDF conversion. Triggers: long context, context rot, large codebase, many files, all files, big document, multi-document, PDF, aggregate, summarize everything, codebase-wide, multi-hop, recursive, sub-agents, map-reduce.
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。
Expert product launch strategist for SaaS and technology companies. Use when planning product launches, coordinating cross-functional launch teams, managing beta programs, creating launch communication plans, planning launch day execution, setting up post-launch monitoring, running launch retrospectives, or defining launch metrics. Covers launch tiering, internal enablement, rollback planning, and contingency strategies.
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。
Expert competitive intelligence and strategy guidance for B2B/SaaS companies. Use when conducting competitive research, creating battlecards, analyzing win/loss data, building market landscape maps, positioning against alternatives, handling competitive objections, writing comparison pages, or developing sales enablement for competitive situations. Use for competitive monitoring, feature comparisons, and market intelligence gathering.
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。
Expert product management guidance for day-to-day PM work. Use when creating roadmaps, prioritizing features, managing stakeholders, planning sprints, grooming backlogs, scoping features, planning releases, defining OKRs, managing technical debt, or coordinating go-to-market. Covers RICE, ICE, MoSCoW frameworks, cross-functional collaboration, and product metrics.
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。
Generate images and video from text prompts via the mediagen CLI, across Gemini, OpenAI and Kie AI. Use when asked to create, generate, render, or edit an image or a video — a logo, an illustration, a mockup, a photo, a banner, a clip — or to mark existing media as AI-generated. Also covers choosing a provider or model for a generation task.
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。
Release tdmcp: write the Keep-a-Changelog entry, bump the SemVer version across every manifest, then (autonomously, per project policy) commit, tag, and push — gated on a td-qa PASS, with hard git safety rails. Use when releasing/shipping/cutting a tdmcp version, writing the CHANGELOG, bumping the version, or tagging a release.
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。
Verification methodology and gate checklist for the tdmcp Connectors Directory submission — run the docs build, build and inspect the .mcpb bundle, sweep for stale .dxt references, and cross-check the form-answer draft against the real requirements. Use to validate the submission package before a human submits, by executing commands and quoting evidence, not by trusting that work was done.
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。
How to migrate the tdmcp Claude Desktop bundle from legacy .dxt to .mcpb (MCP Bundle) and keep it building — covers the manifest schema (verify against the installed packer, never hardcode), the build-mcpb.mjs packer/zip-fallback flow, the npm scripts, and the full .dxt→.mcpb reference sweep across docs and scripts. Use when packaging or migrating the tdmcp desktop bundle.
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。
Consolidate the five tdmcp surveyor reports into one prioritized FEATURE_BACKLOG.md — dedupe cross-surface overlaps, reconcile every candidate against the roadmap (NEW vs planned vs extension), rank by a selectable impact×effort weighting profile into P0/P1/P2 (high-confidence first), and emit per-surface tables + a recommended-next shortlist that hands straight to the build pipeline. Use when a td-synthesizer agent is consolidating surveys during the feature-discovery harness.
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。
Consolidate the td-trend-scout reports under `_workspace/hype-scout/` into one prioritized HYPE_TOOL_BACKLOG.md — dedupe trends across surfaces, vet each candidate against the real tdmcp codebase (layer fit, operator coverage, bridge work), rank by Hype × Build-Ease, and emit a 'Ready for tdmcp-pipeline' top-5. Use when a td-hype-synthesizer agent is consolidating scouts at the end of the tdmcp-hype-scout harness.
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。
Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.
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。
Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline instead.
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。
How to migrate the tdmcp Codex Desktop bundle from legacy .dxt to .mcpb (MCP Bundle) and keep it building — covers the manifest schema (verify against the installed packer, never hardcode), the build-mcpb.mjs packer/zip-fallback flow, the npm scripts, and the full .dxt→.mcpb reference sweep across docs and scripts. Use when packaging or migrating the tdmcp desktop bundle.
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。
Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.
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。
Quality-assure integrated tdmcp features: run the four PR gates + recipe/bridge tests, cross-boundary coherence checks (tool schema↔CLI↔docs↔registry, operator↔createable, bridge↔client), and live TouchDesigner validation (preview + post-cook error check) when the bridge is reachable. Use when validating/QA-ing/testing tdmcp tools, checking a feature actually cooks in TD, verifying CLI matches a tool, or gating a release.
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。
Cloud control-plane exploitation for AWS, Azure/Entra, GCP, and Alibaba Cloud: IAM/RAM privilege escalation, impersonation, cross-account trust, serverless/compute control, and cloud-native persistence. Host OS persistence/C2 after root/SYSTEM belongs to /post. K8s RBAC belongs to /k8s. Operator chooses next modules; new identities default to /cloud-recon first.
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。
Excellence-first strategic decision support. This skill should be used when users need to choose between options, pressure-test a plan, evaluate risk, or make a specific decision — across security, product, growth, operations, org design, and finance. Use when there is a decision with tradeoffs to score and a recommendation to make. For pure research ("what does the best in the world do about X?"), use best-in-world-research instead.
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。
Multi-backend database security auditor. Audits Supabase, Firebase (Firestore/RTDB/Storage/Functions/Remote Config), MongoDB (self-hosted + Atlas), self-hosted PostgreSQL, and self-hosted MySQL for RLS/rules misconfigurations, exposed credentials, auth bypasses, MongoBleed (CVE-2025-14847), pgBouncer CVE-2025-12819, mysql_native_password drift, ghost auth, and storage exposures. Use this skill whenever the user mentions database security, RLS or rule audits, security review, penetration testing a vibe-coded app, checking if their DB is exposed, hardening a backend, fixing security rules, or auditing apps built with Lovable/Bolt/Replit/Cursor/Claude Code on any of these backends. Trigger on phrases like 'is my app secure', 'check my database', 'audit my Firebase', 'audit my MongoDB', 'audit my Postgres', 'audit my Supabase', 'is my DB exposed', or any cross-backend variant ('audit my full stack').
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。