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概要と使いどころ
Classify Alchemy authentication, JSON-RPC, Data API, throughput, and partial-response failures before applying bounded recovery. Use when an Alchemy integration fails or degrades. Trigger with "Alchemy error", "Alchemy 429", or "debug an Alchemy request".
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 Algolia request, credential, index, task, and query failures from concrete evidence. Use when an integration returns 4xx or 5xx responses, stale results, or unexpected empty hits. Trigger with "debug Algolia error", "Algolia 403", or "Algolia search failed".
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。
Collect a bounded, secret-safe Algolia diagnostic bundle for an incident or support escalation. Use when a reproducible search or indexing failure needs portable evidence. Trigger with "Algolia debug bundle", "collect Algolia diagnostics", or "Algolia support evidence".
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。
Build a minimal, reviewable Alchemy EVM read with viem and prove its network, authentication, and failure behavior. Use when starting an Alchemy integration or replacing an SDK sample. Trigger with "Alchemy hello world", "read an Ethereum block", or "test my Alchemy connection".
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。
Triage Abridge recording, note-review, Epic handoff, and access failures from observed evidence without inventing vendor error codes. Use when an Abridge clinical workflow is degraded. Trigger with "diagnose this Abridge issue".
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。
Classify Adobe failures from redacted response evidence and select the smallest bounded recovery. Use across auth, Firefly, Photoshop, PDF Services, Events, and App Builder. Use when the task requires adobe response-led error triage. Trigger with "fix Adobe error", "Adobe 403", or "Adobe API failed".
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。
Build a local synthetic rehearsal for customer-owned Abridge workflow adapters and failure states. Use when developing integration code without access to patient data or a documented public Abridge sandbox. Trigger with "create an Abridge dev loop".
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 when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).
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。
Monitor a PR's CI checks and Greptile code review after submission. Polls CI status, auto-fixes failures via ralph-loop, waits for Greptile review, addresses comments, and iterates until green.
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。
Role profile — a reviewer who is fact-seeking, bedrock-seeking, honest, and rejecting. Demands that arguments rest on small facts that cannot be wrong (not on stacked assumptions dressed up as foundation), and that deliberately-unclear concepts be quarantined — never leaked into solid layers, never mixed with each other. Catches the failure mode where designs ship after partial grounding: most of the spec researched, the design feels finished, and the unresearched remainder holds the deal-breaker. Invoke with `/pedantic <target>` (e.g. `/pedantic review this design doc`, `/pedantic review the SDK design`, `/pedantic review this PR`). Probes cover logical structure (definitions, assumptions, boundaries, contradictions, unfalsifiability, vague quantifiers, counterexamples), epistemic honesty (researchable vs. discoverable-only-by-doing), bedrock integrity (assumed-bedrock, leaked uncertainty, mixed unclarity), and design pathology (YAGNI, wrong-layer abstraction, unclear responsibility, fragmentation, over-engineering). Use when you want a hard critique of a plan, design doc, technical doc, code change, or PR description — not a copy edit, not a vibe check.
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。
Discipline for the seam between two SDKs (or two sides of one contract) that the same hand writes. The failure mode: "we own both sides" produces dirty contracts no foreign reviewer would accept. The exercise: pretend the other side is FFI, IPC, or a network protocol you cannot rewrite. Spawn an adversarial subagent profiled as the producer's maintainer; negotiate the change as a feature request, not a PR. Companion to $sdk-design. Language-agnostic — applies to a TS package + its consumer, a Rust crate + its WASM binding, two services sharing a wire format, or any other boundary the same author writes both ends of.
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。
Guides work on the Figma I/O package (@grida/io-figma, packages/grida-canvas-io-figma/). Covers the fig-kiwi binary parser, Kiwi→REST→Grida conversion pipeline, fig2grida CLI, REST API JSON conversion, and testing with clipboard/fig/REST fixtures. Use when adding node type support, fixing conversion bugs, extending fig2grida, working on the fig-kiwi parser, writing tests for Figma import, or debugging clipboard paste failures after a Figma update.
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。
Compile current scholarly evidence for a scientific manuscript or research brief. Use when the user explicitly asks to gather literature, references, background evidence, competing findings, or a manuscript research packet. Uses Parallel Search by default, Parallel Extract for source verification, Parallel Research for explicitly deep/exhaustive work, optional explicit Parallel Chat, and optional Perplexity only when requested or allowed as a failure fallback.
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。
Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "deployment pipeline", "chaos engineering", "retry storm", "health checks", "my service keeps crashing", "prevent cascading failures", or "make it resilient". Also trigger when designing resilient microservices, planning zero-downtime deployments, or capacity-planning for peak load. Covers stability patterns, capacity planning, deploy/release decoupling, and observability. For data systems, see ddia-systems. For system architecture, see system-design.
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。
Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation". Use when the user mentions "pricing", "how much should we charge", "willingness to pay", "pricing page", "packaging", "freemium vs free trial", "are we leaving money on the table", "nobody buys at this price", "price increase", or "good-better-best". Also trigger when designing or auditing pricing and packaging, validating willingness to pay before building, segmenting customers by value, or choosing between subscription, usage-based, and freemium models. Covers price-before-product, willingness-to-pay talks, the four failures (feature shock, minivation, hidden gem, undead), leader/filler/killer packaging, and behavioral pricing. For offers and guarantees, see hundred-million-offers. For what customers value, see jobs-to-be-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。
Use when writing, reviewing, or debugging Terraform/OpenTofu modules, tests, CI, scans, or state ops - diagnoses failure mode (identity churn, secrets, blast radius, CI drift, state corruption) with version-aware guards.
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。
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
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。
Analyze tau2-bench task export files to identify exactly where and why tasks failed. Map failures to specific conversation rounds, show root causes, check whether relevant documentation was available, and cite sources. Use this skill whenever you need to debug a tau2-bench evaluation, understand why an agent made wrong decisions, identify missing knowledge, or review task performance—especially when context length, eligibility criteria, or policy compliance might be at fault.
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。
Finds the root cause of a bug, test failure, or unexpected behavior before proposing any fix. Use this whenever something is broken and the cause is not yet proven — a failing test, a production error, intermittent behavior, or a symptom that appeared after a change. Also use when a fix has been attempted and did not work, or when the same bug keeps coming back.
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。
Designs and runs cloud infrastructure — environments, infrastructure as code, networking and isolation, scaling, and cost. Use this to design a cloud environment, control infrastructure spend, set up environment separation, plan for scale or region failure, or review infrastructure someone configured by hand.
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。
Makes systems debuggable and reliably operable — instrumentation, alerting that is worth waking for, service objectives, and learning from failure. Use this to instrument a service, fix alerting that is ignored, set error budgets or reliability targets, prepare for on-call, or run a blameless post-incident 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。
Manages the flow of goods and inputs — sourcing, inventory, lead times, fulfillment, and supply risk. Use this to reduce stockouts or excess inventory, plan for a supplier failure, decide reorder points and safety stock, improve fulfillment reliability, or assess concentration risk in a supply base.
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。
Plans for operating through disruption — impact analysis, recovery objectives, continuity plans, and the exercises that prove they work. Use this to run a business impact analysis, set RTO and RPO, write or test a continuity plan, prepare for a supplier or site failure, or answer a customer's resilience questionnaire.
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。
Designs, documents, and fixes operational processes — mapping the current state, finding where work actually stalls, redesigning the flow, and building controls that hold. Use this when the same failure keeps recurring, when a handoff between teams is unreliable, when onboarding a repeated task, when work takes far longer than the work itself, or when deciding whether to automate, standardize, or eliminate a process.
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。