ripple
Use before changing a public function/signature/schema/API to see the blast radius. "If I change X, what else changes". Reads call graph + tests + docs + memory for prior similar changes.
What this skill does
# ripple Change-impact visualisation. Walks the call graph, finds tests that would change, finds docs that would lie, surfaces the full blast radius before you commit. ## Method 1. **Anchor.** What's changing — function signature, public method, schema, env var, config key, API endpoint, file location? 2. **Direct refs.** `Grep` / native search for the symbol/string. Categorise hits: - **Producers** — write/emit this - **Consumers** — read/call this - **Tests** — assert behaviour about this - **Docs** — describe this to humans - **Generated** — codegen, snapshots, fixtures 3. **Transitive.** For each consumer, check if **its** behaviour changes. Walk one more hop. Stop at module boundaries unless a public API of the consumer is also affected. 4. **Memory.** `mem_search` for prior changes to similar APIs. What broke last time? What was forgotten? 5. **Report.** Tree-shaped impact map. ## Output shape ``` Anchor: <symbol / endpoint / config> Direct impact: Producers: N — <file:line list> Consumers: N — <file:line list> Tests: N — <file:line list> Docs: N — <file list> Generated: N — <list> Transitive impact (1 hop): <consumer file> → also publicly exposes signature change to <its callers> ... Memory: Prior similar change at <commit/summary>: <what broke, what was forgotten> Risk: <low | med | high> Pre-flight checklist: ☐ Update direct callers ☐ Update tests ☐ Update docs (README, API ref) ☐ Regen fixtures/snapshots ☐ Migration note in CHANGELOG ☐ <items derived from memory of past misses> ``` ## Rules - **Walk the graph; don't guess.** Every consumer cited with file:line. - **Tests count even when adapter-shaped.** Snapshot tests, contract tests, integration — all flagged. - **Generated code is the silent killer.** Always check. - **Memory ALWAYS consulted.** Past incidents reveal the items most easily missed. ## Anti-patterns - "Should be safe" without enumeration - Skipping tests in the count (they're code that depends on the symbol too) - Ignoring docs (lying docs erode trust) - Walking too deep (3+ hops dilutes signal) ## When NOT to use - Internal-only function with one caller — manual scan suffices - Changing implementation without changing signature — no ripple - Pre-merge after the change is done — too late, this is preflight ## Subagent dispatch - `Explore` for the grep + call graph - `general-purpose` for transitive walk ## Value over native CC CC will grep for callers if asked. CC won't naturally categorise into producers/consumers/tests/docs/generated, walk transitively with discipline, or cross-reference memory of past changes. The structured pre-flight IS the value.
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.