groove-utilities-task-create
Create a new task in the configured backend.
What this skill does
# groove-utilities-task-create ## Outcome A task is created in the configured backend with a title, type, status, optional parent, and (for non-trivial tasks) a rich body. The task ID is returned for reference. This command is the single source of truth for how tasks are created — other skills (work compound, daily, etc.) that need to create tasks must follow this spec and call this skill rather than defining their own creation rules. ## Acceptance Criteria - Task exists in backend with all required fields populated - Task ID is shown to user after creation - Non-trivial tasks (feature work, bugs, plans, stage tasks) have a rich body — never create with an empty body when the task represents real work or a stage - Parent is set when context suggests one (e.g. stage task under a daily or work epic) ## Constraints - Read `tasks.backend` from `.groove/index.md` to determine backend - If `tasks.backend: none`, no-op with friendly message - If title not provided in arguments, ask user for title and type before proceeding - Infer parent from current context (open tasks, recent work) and confirm with user if ambiguous - Default status is `in-progress` (not `todo`) — tasks are created when work is being done - Do not auto-mark any task as completed during creation - Backend mappings: - `beans`: `beans create "<title>" -t <type> --parent <id> -s in-progress`; body via `beans update <id> -d "<body>"` or by editing the task file under `.groove/tasks/` if the backend is file-based - `linear`: create issue via linear CLI or MCP with appropriate team/project - `github`: `gh issue create --title "<title>" --body "<body>" --milestone <milestone>` - **Body (standard):** For any non-trivial task, always supply a body. Use the backend's body/description field (or task file content). Standard body sections: **Context** (what work or session this task belongs to), **Goal** (what "done" means at a high level), **Acceptance Criteria** (checklist of concrete conditions), **Links** (to CHANGELOG, specs, learned files, or other artifacts). Omit a section only if it truly does not apply. - **Type:** Use the backend's types (e.g. beans: `task`, `bug`, `feature`, `epic`, `milestone`). Stage and bookend tasks (daily Start/End, work stages such as "YYYY-MM-DD, Compound — topic") use type `task` when the backend has no `chore` (e.g. beans). - **Hierarchy:** Set parent when the task is part of a larger unit (e.g. a daily, an epic). If the caller does not specify a parent, infer from context when possible. - Always echo the created task ID and title back to the user
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.