proyecto26
OrganizationSherlock AI plugin; Research & Implementation Supercharged with a curated list of AI skills
Categories
Indexed Skills (28)
deep-research
Generate format-controlled research reports with evidence tracking, citations, and iterative review. This skill should be used when users request a research report, literature review, market or industry analysis, competitive landscape, policy or technical brief, or require a strict report template and section formatting that a single deepresearch pass cannot reliably enforce.
genimg-gemini-web
Image generation skill using Gemini Web. Generates images from text prompts via Google Gemini. Also supports text generation. Use as the image generation backend for other skills like cover-image, xhs-images, article-illustrator.
paper-analyzer
Transform academic papers into in-depth technical articles with multiple writing style options. Use the MinerU Cloud API for high-precision PDF parsing, automatically extracting images, tables, and formulas. Optional formula explanations and GitHub code analysis, generating Markdown and HTML formats.
paper-comic
Generate educational comics from academic papers, using visual storytelling to explain core ideas and innovations. Supports 4 art styles: classic (clean lines), tech (futuristic), warm (friendly), chalk (blackboard). Uses genimg-gemini-web to generate images.
paper2code
Analyzes research papers (PDF/arXiv URL) and converts them into executable code. Automatically activated upon requests for paper replication, algorithm implementation, or research reproduction. Responds to requests like "Implement this paper", "paper2code", "Convert paper to code".
visual-architect
Transform research papers into professional visual schemas. Analyzes paper logic, selects optimal layout patterns, and generates detailed prompts for AI image generation.
api-design
This skill should be used when the user needs to "design the API", do "endpoint design", pin down a "request/response shape", choose a "pagination" strategy (cursor vs offset), add an "idempotency key" to a write, plan "API versioning", an "error contract", or pick between "REST vs gRPC vs GraphQL" or "WebSocket vs polling". Use it whenever a design has reached the interface — the concrete request, response, primary access path, and how clients page, retry, and version — even if the user only said "the boxes talk to each other".
architecture-diagram
This skill should be used when a system design needs a diagram — "draw the architecture", "diagram this system", "show the components", "make an architecture/infrastructure/topology diagram", or visualizing boxes-and-arrows, data flow, regions, or failure paths for a design. It generates a self-contained dark-theme HTML + SVG diagram (with PNG/PDF export). Use it whenever the `system-design` orchestrator or a building block reaches the "draw it" step, even if the user doesn't say "diagram".
back-of-the-envelope
This skill should be used when the user needs to "estimate QPS", "back-of-the-envelope" (BOTEC) numbers, "how much storage / bandwidth", "how many servers", "peak load", "capacity planning", or wants the standard latency / throughput / availability numbers to ground a design (latency table, QPS rates, powers of two, nines). Use it whenever a design decision hinges on scale — convert any "high traffic" / "huge data" phrase into concrete numbers before choosing components, even if the user doesn't say "estimate".
blob-store
This skill should be used when the user wants a "blob store" or "object storage", names "S3" or an S3-compatible store, needs to "store images / video / files", asks about "multipart upload" or "resumable upload", "signed / presigned URLs", "media storage", "unstructured data at scale", object "versioning", storage "tiering" (hot/cold/archive), or "erasure coding" vs replication for durability. Use it whenever a design must hold large unstructured objects (photos, video, backups, logs, ML datasets) and serve them cheaply and durably, even if the user just says "where do we put the files".
caching
This skill should be used when the user asks about a "caching strategy", "cache invalidation", "what to cache", "read-through vs write-through vs write-back", "cache eviction" (LRU/LFU/TTL), "Redis vs Memcached", "stale reads", or hits "thundering herd", "cache stampede", "cache penetration", or "hot key" problems. Use it whenever a design is read-heavy or a datastore is overloaded by reads, even if the user doesn't say "cache".
consistency-coordination
This skill should be used when the user asks about the "CAP theorem", "PACELC", a "consistency model", "eventual vs strong consistency", "read-your-writes", "causal consistency", "quorum" or "R+W>N", "consensus", "Raft / Paxos", "leader election", "consistent hashing", a "distributed transaction", "2PC", or "saga". Use it whenever a design has multiple copies of data or coordinating nodes and a decision hinges on what a reader is guaranteed to see during replication lag, a network partition, or a node failure — even if the user doesn't say "consistency".
content-delivery
This skill should be used when the user asks about a "CDN", "edge caching", "static asset delivery", "media / video delivery", "geo distribution of content" or "edge POP selection", "push vs pull CDN", "cache-control headers" / "TTL for static assets", "origin offload", or "origin shield". It gives the recipe for serving bytes from the edge close to users. Use it whenever a design serves images, video, JS/CSS, or downloads to a wide geography, or the origin is saturated by repeat reads of the same files, even if the user doesn't say "CDN".
data-storage
This skill should be used when the user asks "SQL or NoSQL", "which database", how to design a "data model" or "schema design", picks an "indexing" strategy, needs "sharding" or "partitioning", sets up "replication" (leader-follower / multi-leader), defines a "primary key"/"sort key", asks whether to "denormalize", or weighs "polyglot persistence". Use it whenever a design must decide where records live, how they are keyed and accessed, and how the store scales past one node — even if the user just says "store the data".
distributed-logging
This skill should be used when the user designs "distributed logging", "log aggregation", "centralized logs", an "ELK" or "EFK" stack, "log shipping", "structured logging", a "correlation ID" or "trace ID" in logs, "log retention", or "high-volume log ingest". It gives the collect → buffer → ship → index → store → retain pipeline, sampling, ordering, and cold-storage tiering. Use it whenever many services emit logs that must be searched in one place under load, even if the user doesn't say "logging pipeline".
distributed-search
This skill should be used when the user designs a "search system", needs "full-text search", asks about an "inverted index", "Elasticsearch / OpenSearch", "relevance ranking" (TF-IDF/BM25), "search autocomplete / typeahead", an "indexing pipeline", or "faceted search". It gives the crawl/index/search architecture, index sharding and replication, ranking, and near-real-time indexing. Use it whenever users must query text by relevance rather than fetch rows by key, even if they don't say "search engine".
dns
This skill should be used when the user asks about "DNS", "domain resolution", "GeoDNS / geo routing", "latency-based routing", "weighted / failover routing", "Route 53 / Cloud DNS", an "A/CNAME/ALIAS record", "anycast", or "DNS TTL / propagation". It gives the global front door that maps a name to the right IP and steers users to the right region or endpoint. Use it whenever a design must direct traffic across regions/data centers, do health-checked failover at the name layer, or expose a stable hostname even if the user doesn't say "DNS".
load-balancing
This skill should be used when the user adds a "load balancer", asks about "L4 vs L7" (transport vs application layer), picks a balancing algorithm ("round robin", "least connections", "weighted", "IP hash"), configures "health checks", needs "sticky sessions" / "session affinity", adds a "reverse proxy", does "SSL/TLS termination", spreads "traffic distribution" across an "autoscaling group", or wants a stateless web tier behind a single entry point. Use it whenever a design has more than one server behind one address, or a single box is the entry-point bottleneck or SPOF, even if the user doesn't say "load balancer".
messaging-streaming
This skill should be used when the user designs a "message queue", reaches for "Kafka", "RabbitMQ", "SQS", "Kinesis", "pub/sub", or "event-driven" architecture, asks about "async processing", "background jobs", "stream processing", or wrestles with "exactly-once vs at-least-once", "delivery guarantees", "message ordering", "duplicate handling / dedup", "dead letter queue", "backpressure", "saga orchestration", or "durable workflow". Use it whenever a slow or spiky operation should move off the request path, or two services must be decoupled, even if the user doesn't say "queue".
observability
This skill should be used when the user asks about "observability" or "monitoring", what "metrics, logs, and traces" to collect, "health checks" (liveness/readiness), "alerting" or "on-call", "SLO/SLI" or "error budgets", the "RED" or "USE" method, "dashboards", or names a tool like "Prometheus", "Grafana", or "Datadog". Use it whenever a design has no answer to "how would we know this is broken?" or "what do we alert on?" — i.e. any time failure would be invisible until users complain, even if the user doesn't say "observability".
requirements-scoping
This skill should be used when the user needs to "clarify requirements", separate "functional vs non-functional requirements", "scope the problem", figure out "what questions should I ask", state the "requirements for <X>", or otherwise pin down a vague design prompt before building. It turns an ambiguous ask into functional requirements, non-functional constraints, and an explicit out-of-scope. Use it whenever a prompt is broad or under-specified ("design Twitter", "build a chat app") even if the user doesn't say "requirements".
resilience-failure
This skill should be used when the user asks about "fault tolerance", "resilience", a "circuit breaker", "graceful degradation", "retry storm" or "thundering herd on recovery", "exponential backoff with jitter", "timeout", "bulkhead", a "single point of failure" (SPOF), "failover", or "rate limiting" (token bucket / leaky bucket / sliding window). Use it whenever a design must keep working through node crashes, slow dependencies, traffic spikes, or partial outages — i.e. any time the answer to "what happens when this breaks?" is missing, even if the user doesn't say "resilience".
scaling-evolution
This skill should be used when the user asks "how does this scale", "scale to millions", "scaling roadmap", "where is the bottleneck", "what breaks first", "10x growth", "vertical vs horizontal scaling", "scale from zero", or "what's the next scale curve". It gives the order-of-magnitude evolution path (single server → tiers → replicas → cache → CDN → stateless tier → multi-region → sharding) and a way to diagnose the *next* bottleneck instead of memorizing one big diagram. Use it whenever a design must grow by orders of magnitude or a load increase is on the table, even if the user doesn't say "scaling".
sequencer
This skill should be used when the user needs a "unique ID generator", "distributed IDs", a "Snowflake ID", asks "UUID vs auto-increment", wants a "time-sortable ID", a "monotonic sequence", a "ticket server", or "ID generation at scale". It gives a menu of ID schemes (UUID/ULID, Snowflake-style, DB ticket/range) with their causality, ordering, and clock-skew trade-offs. Use it whenever a design needs collision-free identifiers across many nodes, even if the user doesn't say "sequencer".
service-decomposition
This skill should be used when the user asks "monolith vs microservices", how to "split into services", set "service boundaries", find the right "service granularity", design an "API gateway / BFF", do "service discovery" or add a "service mesh", or worries that services are "too chatty" / "too fine-grained". It gives the recipe for carving a system into services (or deciding not to) and wiring how they find and call each other. Use it whenever a design has more than one service — or someone is tempted to add more — even if the user doesn't say "microservices".
sharded-counters
This skill should be used when the user needs a "sharded counter", "distributed counter", to "count likes / views at scale", handles a "high-write counter" or "hot counter contention", asks about "approximate counting", "real-time counts", or "HyperLogLog". It gives the recipe for absorbing write-heavy counting without a single hot row. Use it whenever one row/key takes concurrent increments faster than it can serialize them, even if the user doesn't say "sharded counter".
system-design
This skill should be used when the user asks to "design a system", "design <a product>" (e.g. "design WhatsApp", "design a URL shortener", "design a news feed"), "high-level architecture for…", "how would you architect…", "system design interview", or wants to scope, diagram, and justify a backend/distributed-system design. It runs a reasoning loop — clarify, estimate, design, weigh trade-offs, stress-test, iterate — and routes to focused building-block skills. Use it whenever a request is an open-ended design problem, even if the user doesn't say "system design".
task-scheduling
This skill should be used when the user designs a "task scheduler", "job scheduler", "job queue", "cron at scale", "distributed cron", "delayed / scheduled / recurring tasks", a "worker pool", reaches for "Celery / Sidekiq / Airflow", or wrestles with "task leasing", visibility timeouts, job priorities, fairness, or duplicate task execution. Use it whenever work must run later, on a schedule, or be reliably leased to a pool of workers, even if the user doesn't say "scheduler". (For plain queue transport and delivery guarantees, that is `messaging-streaming`.)
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.