Claude Code eklentileri
Genel Claude Code pazaryerlerinden 95 eklenti. Her biri birlikte yüklenen beceriler, eğik çizgi komutları, ajanlar, kancalar veya MCP sunucuları içerir.
Bu filtrelere uyan 95 eklenti gösteriliyor. Filtreleri temizleyin
Curate auto-memory, promote learnings to CLAUDE.md and rules, extract patterns into skills. Ships 5 slash commands (/si:memory-review, /si:promote, /si:extract, /si:memory-status, /si:remember) and 2 sub-agents (memory-analyst, skill-extractor).
Stop re-explaining your notes to Claude. Turns your Obsidian vault into memory Claude can actually search, and keeps it true: new sources rewrite existing pages, contradictions reconcile, and stale facts get flagged. AI note-taking and PKM for Claude Code.
120 marketing skills and 8 commands as an AI marketing staff — one plugin, portable skills on 70+ hosts, or an 8-bot team — and as a four-layer operating system: Narrative strategy; SEO/GEO, Organic Social, Email, Paid Ads, and Influencer channels; Product Launch orchestration; and a Protocol layer with seven append-only truth registries plus non-canonical working memory. Eight typed advisory frameworks (TALE, CORE-EEAT, CITE, STAR, ECHO, SEND, ROAS, RAMP) use machine-checkable auditor artifacts and immutable standalone runtime contracts. Keyless-first and zero-dependency.
Executive-function & focus skills for getting unstuck and running your own brain: beat activation-energy paralysis, triage overwhelm, protect your energy, build a personal memory file, and make hard decisions when depleted. ADHD-friendly, useful for everyone.
Cross-profession skills: Press Release, Grant Proposal, Executive Summary, Teaching Lesson Plan, Sycophancy Challenger, Last 30 Days Research, NotebookLM Connector, Professional Brain, Action Runner. Get genuine push-back on your ideas, gather multi-platform research, automate NotebookLM — plus the Professional Brain: a durable local memory skills read & write back (provenance-tagged), and Action Runner to execute a skill's recommendations (open tickets, post updates) safely behind a dry-run approval gate.
NVIDIA DGX Spark (GB10) environment operations. Use when setting up, preflighting, or debugging ML workloads on DGX Spark or aarch64 Blackwell hardware — CUDA-13 wheel/ABI checks, unified-memory OOM ladders, thermal monitoring.
Study companion for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org. Twenty chapter files, a glossary, patterns and a cheatsheet index the whole book, and a delta reference dates it against 2026 practice with per-claim confidence levels: double descent qualifying the U-curve, AdamW splitting weight decay from L2, transformers displacing Chapter 10's recurrence, diffusion growing out of Chapter 18's score matching. Four stdlib tools make it executable — a prerequisite-closed reading-path planner that refuses goals the book does not cover, a training diagnostic running Chapter 11's rules in priority order so a NaN is never reported as overfitting, a capacity planner that ranks 'shrink the model' last when overparameterized, and a parameter/FLOP/activation-memory calculator that refuses a stack whose shapes do not connect. A companion, not a compilation: the book is copyrighted, so nothing here reproduces its text.
Answer questions about past agent runs from the recording, not from memory. Three read-only stdlib scripts over the session transcripts Claude Code and Codex already write: a finder that locates the run by repo, time window, touched file or command text; a timeline that numbers every step with its exit code, lists every file changed (flagging changes the agent never mentioned) and walks back from any step with each causal edge labelled recorded or inferred by a named rule; and a claim checker that tests a summary's claims (ran, passed, edited, not-edited, read) against the run and catches tests that passed before a later edit and exit codes that belong to the last command of a pipe. Secrets are always redacted. A UserPromptSubmit hook gives the agent this session's transcript path when a prompt asks about past work. Ships cs-run-forensics agent, /cs-run-forensics and /cs-check-claims commands and 3 cited references.
Engineer an agent's forgetting, not just its remembering. Four deterministic stdlib scripts implement the four lenses of agent memory: a cost profiler that splits construction from query spend and reports cost per correct answer (construction energy exceeds total query energy across 300 queries in the Stanford characterization); an architecture picker that scores the four paradigm families — long-context, flat RAG, structure-augmented RAG, agentic — disqualifies on hard constraints, names the cost the winning choice makes you pay, and refuses to pick when the top two tie; a density auditor that classifies every record in a memory directory or JSONL export as FACT / SKILL / LOG / PROSE, finds near-duplicates, and flags stale wording; and a forgetting-policy linter that fails any design with no forgetting rule. Ships cs-memory-engineer agent, /cs-memory-engineering and /cs-forgetting-audit commands, 4 references, and a seven-question forcing worksheet.
A four-tier memory ladder for Claude Code where promotion is earned by recurrence, not asserted by confidence. L0 raw transcripts are never injected; L1 candidate atoms are gitignored and recalled on lexical relevance per prompt; L2 project context loads each session start; L3 stable persona is always loaded. L1 to L2 needs three distinct sessions spanning two distinct calendar days (a stated claim needs two; a verified claim is the only single-observation path); L2 to L3 needs two projects and thirty days. Two gates refuse rather than guess: a claim altered by the redaction pass never promotes on evidence alone, and a contradicted claim freezes until a human resolves it. Three hooks run the loop unattended and every one fails open. Nothing reaches a committed CLAUDE.md without an explicit human adopt. Ships 5 stdlib scripts, 3 hooks, a cs-memory-curator agent, /cs-memory, a JSON schema, and a 69-check validator. Concept from TencentCloud/TencentDB-Agent-Memory (MIT); no upstream code
Digital forensics and incident response framework with 14 specialized agents covering target profiling, evidence acquisition, log/memory/container/cloud analysis, IOC extraction, and reporting.
Nightly offline self-evolution for this repo's Claude agent: harvests past Claude Code sessions (read-only), mines recurring tasks, replays them offline on your own API budget, and consolidates learnings into validated CLAUDE.md memory and SKILL.md skills behind a held-out gate, staged for review (never auto-applied). Verbatim vendor of microsoft/SkillOpt's stdlib-only skillopt_sleep engine + Claude Code plugin surface (MIT).
Redis development best practices — data structures, Redis Search (lexical + vector + hybrid retrieval), caching, and performance optimization, plus Redis Iris (Agent Memory, Agent Playbooks, Context Gateway, Intent Router, Lens), and live lookup of the official redis.io documentation.
Engineering discipline for AI coding agents: question the request, verify against current docs instead of memory, plan, build test-first on the cheapest capable model, review with a second model family, prove it before saying done
Comprehensive Rust security code review with specialized bug-finding agents covering the safe/unsafe boundary, memory safety in unsafe blocks, concurrency, panic-induced DoS, recursion-induced stack overflow, FFI, and async runtime hazards
Persistent memory plugin for Claude Code - remembers preferences, decisions, and corrections across sessions and context limits
Cortex — persistent memory and cognitive profiling for Claude Code (renamed from the 'cortex' plugin in v4.15.0 to match the PyPI/MCP-registry identity hypermnesia-mcp) — thermodynamic memory with heat/decay, intent-aware retrieval, biological plasticity, codebase intelligence, and cognitive profiling. These mechanisms are implemented and inspectable; committed ablations do not establish a retrieval gain from all 36 mechanisms. 57 MCP tools (60 with the optional ai-architect-mcp-codebase + ai-architect-mcp-spec integrations) with enriched schemas (visualization extracted to the standalone Hypermnesia MCP Viz server). PostgreSQL + pgvector in CLI mode; automatic SQLite fallback in Cowork/sandboxed mode. v3.17.0 — autonomous per-project wiki: SessionStart auto-spawns a 6-hour consolidate cycle; a headless `claude -p` worker drains the curation-gap queue, calls codebase-intelligence MCP tools to ground each section in the real call graph, and authors missing anchor pages (architecture / s
ARM Cortex-M firmware development for Teensy, STM32, nRF52, and SAMD with peripheral drivers and memory safety patterns
Seventeen skills that ship as one pack — a portable discipline for tracked, multi-session, agent-assisted development: the orchestrator seat a non-engineer works from (one session routing, auditing, and merging parallel lanes), a router entry point, a once-per-repo setup interview that records whether you lead from that seat or read code and pick skills, per-repo institutional memory written as side effects of work, relentless grilling, decision maps, throwaway prototypes, autonomous research lanes, ticket filing, human-step wizards, session handoffs, a build discipline of seam-scoped test-first tracer slices, a disciplined bug-diagnosis loop where no fix ships without a named cause, an adversarial review that breaks changes before they ship, a skeptic-verified state review of the codebase itself, an append-only decision trail that lets a human audit an unattended run after stepping away, and a PR-writing standard that leads with the problem, shows before-and-after proof, and says whet
Agent-native marketing playbook CLI: 76 skills, 7 research/review agents, brand memory, and /cmo orchestration.