One search for your own team's files and the public ecosystem. See how real projects write their agent instructions, and bring the good ideas home.
vxcontrolCLAUDE.mdvxcontrol/pentagi/CLAUDE.md
password reset, API token generation, etc.), enforce the same policy in **both** backend and frontend — never rely on frontend validation alone. Source of truth, keep the two in sync: `backend/pkg/server/models/init.go
JetBrainsSkillJetBrains/intellij-community/.agents/skills/module-set-pluginization/SKILL.md
Convert Product DSL module sets into bundled wrapper plugins.
JetBrainsSkillJetBrains/intellij-community/.claude/skills/module-set-pluginization/SKILL.md
Convert Product DSL module sets into bundled wrapper plugins.
JetBrainsAGENTS.mdJetBrains/intellij-community/java/AGENTS.md
java-impl` holds the code insight: the completion, the intentions, and the refactorings. - `java-frontend`, `java-backend` and `java-frontback-impl` serve the split mode. Read the `remote-dev-code
GoogleSkillgoogle/skills/skills/cloud/application-design-center-design-deploy/SKILL.md
Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.
GoogleSkillgoogle/skills/skills/cloud/cloud-monitoring-chart-generation/SKILL.md
Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.
GoogleSkillgoogle/skills/skills/cloud/cloud-run-alert-configuration/SKILL.md
Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance saturation (warning/critical), container CPU/memory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use gke-alert-configuration) or Compute Engine VMs.
GoogleSkillgoogle/skills/skills/cloud/gemini-live-api/SKILL.md
Generates a Gemini LiveAPI client service class in the user's chosen programming language. Use when the user wants to build, scaffold, or integrate a client that connects to the Gemini Enterprise LiveAPI websocket endpoint, handles session setup/resumption, bearer token refresh, and sending/receiving `ClientMessage`/`ServerMessage` protos. Don't use for general (non-live, non-bidirectional) Gemini API usage such as one-shot `generateContent`, embeddings, image/video generation, or fine-tuning — use the `gemini-api` skill for those.
GoogleSkillgoogle/skills/skills/cloud/google-cloud-solution-build-deploy-agents/SKILL.md
Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.
GoogleSkillgoogle/skills/skills/cloud/google-cloud-solution-n-tier-serverless-web-app/SKILL.md
Assists in designing and implementing secure n-tier serverless web applications and microservices on Google Cloud. Use when users need architecture designs, security checklists, Terraform code, or deployment guidance for multi-tier serverless apps, regional data residency / European sovereignty compliance, zero-trust private VPC networking, or Private Service Connect. Don't use for VM, GKE, or non-Google Cloud architectures.
GoogleSkillgoogle/skills/skills/cloud/google-cloud-solution-rag-enterprise-search-gke-sqldb/SKILL.md
Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.
GoogleSkillgoogle/skills/skills/identity/dpop-adoption/SKILL.md
Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com/token. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM / service account authentication.
kortix-aiAGENTS.mdkortix-ai/suna/AGENTS.md
complete self-host preview for the branch — its own PostgreSQL, Supabase, API, gateway, frontend, and HTTPS origin. This is how work is shared and reviewed internally. **Sharing never requires merging
kortix-aiSkillkortix-ai/suna/.agents/skills/kortix-release/SKILL.md
How to cut a Kortix production release — the versioning philosophy (when patch vs minor vs major) and the exact flow: derive the release title + notes from the FULL git log since the last release, run the Promote workflow, then deploy + verify prod. Load WHENEVER the user wants to release, promote, cut/ship a version, publish a release, or bump the version. The release notes ARE the public /changelog, so they must be 100% accurate to what shipped.
kortix-aiSkillkortix-ai/suna/.agents/skills/testing/SKILL.md
Use for every Kortix test task, behavior change, bug fix, refactor, API route change, CLI change, SDK change, browser journey, test failure, coverage question, local benchmark, or testing infrastructure change. Enforce the single local-first runner, black-box flow contracts, package-local SDK tests, browser-only Playwright tests, and real input/output verification.
PydanticAGENTS.mdpydantic/pydantic-ai/docs/realtime/AGENTS.md
rule lives here), `turns.md`, `tools.md` (tools only), `capabilities.md` (per-hook support story), `history.md`, `deployment.md` (frontend transports), `lifecycle.md` (connection lifecycle only), `observability.md`, `troubleshooting.md` (the symptom-first index — per-page "Edge cases
PydanticSkillpydantic/pydantic-ai/src/pydantic_ai_harness/pydantic_ai_harness/.agents/skills/migrating-deep-agents-to-pydantic-ai-harness/SKILL.md
Migrate Python LangChain Deep Agents applications to Pydantic AI and Pydantic AI Harness. Use when the source uses the upstream `deepagents` package or demonstrably reproduces its middleware, backends, skills, memory, subagents, or sandbox contracts. Use `migrating-langchain-to-pydantic-ai` for plain LangChain, LangGraph, or LCEL migrations and `pydantic-ai-harness` for greenfield Harness usage.
nukeopAGENTS.mdnukeop/nuclear/AGENTS.md
backend lives in `packages/player/src-tauri/src/`. Modules: - `bridge/` - bidirectional RPC. Lets Rust servers call into the frontend (`Bridge::call` emits a `bridge:request` event, frontend replies via the `bridge_respond` command). - `http
Google CloudAGENTS.mdGoogleCloudPlatform/generative-ai/search/gemini-enterprise/ge-demo-generator/AGENTS.md
mixed. Handed a menu of languages, the model sometimes picks one off it. The frontend already knows the intended language — the Template Hub selector, or the research language while research
Google CloudSkillGoogleCloudPlatform/generative-ai/search/gemini-enterprise/ge-migration-agent/skills/SKILL.md
Holds canonical source and target environment parameters and verified DataStore mappings.
Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.
