Calculate the count, sum, minimum, maximum, and average of supplied numbers or datasets, then present the results in a clear, structured format. Analysis results can also be saved to a file when requested.
Prepare a first reply to a customer inquiry by classifying the issue, confirming understanding, and requesting missing details. Use existing documentation for answers, acknowledge feature requests, or route cases that need human follow-up.
Create summaries, briefings, literature reviews, or comparisons from workspace files. Organize findings by topic, support claims with short quotations and file references, and produce a Markdown report with a list of cited sources.
Save the current code state in a local Git commit before risky changes, then return to that checkpoint if needed. Useful for multi-file refactoring and trying another approach after an unsuccessful edit.
Build Java applications with cooperating AI agents using AgentScope Java. Guides asynchronous processing, where waiting tasks do not block execution, plus language model connections, external tools, workflow coordination, error handling, and tests.
Use a starter template to learn how an agent skill is organized and outline its intended use, required inputs, steps, and output format. Replace the placeholder body with your own working instructions before relying on it.
Verify edited code with relevant build commands, type checks, automated code checks, and targeted tests. Finds commands in project configuration, fixes reported problems, and repeats the same checks until they pass.
Answer business questions about counts, trends, comparisons, or rankings using SQL, a language for querying tables. Validate the results, then present a concise answer, a small table, the executed query, and supporting checks.
Apply related edits across several files using a unified diff, a file describing code changes. Check the patch with Git before applying it, and rebuild rejected patches using the current file contents.
Run AI coding command-line tools on behalf of worker agents using their prepared prompts and workspaces. Detect available tools, configure delegation, return results, and apply supported execution controls such as time budgets and permission settings.
Prepare coding tasks for delegation to an authorized agent’s AI command-line tool. Set up and synchronize the workspace, write precise change requests, then review returned changes and run relevant checks before reporting completion.
Coordinate changes to shared task folders with .processing marker files that indicate ongoing work. Managers and Workers check these markers before editing, synchronize files through MinIO, and remove markers after completing their changes.
Clarify responsibilities in a TeamHarness team, including planning, task execution, result acceptance, and runtime administration. Use the role boundaries to identify who owns each action and how participants should handle sensitive information.
Manage communication channels by identifying senders, maintaining trusted contacts, and setting the administrator's primary notification destination. It also covers first contact on a new channel and contacting the administrator across channels, with rules for handling unknown senders.
Find worker agents in Nacos that match a task, recommend candidates, and import the administrator's chosen worker. It also supports importing a specified nacos package URI, with worker name confirmation and direct reporting of installation failures.
Carry out assigned work as a Worker agent, from acknowledging the task to submitting a structured result. Keep deliverables in the task directory, record progress, request decisions when blocked, and publish results to the Task room.
Keep Hermes Worker configuration and shared task files synchronized with MinIO, a central storage service. The skill covers immediate downloads, manual result uploads, and which configuration changes take effect on the next message or require a restart.
Plan how multiple agents should work together. Choose between dependency-based tasks and repeated work cycles, define ownership and acceptance criteria, identify safe parallel work, and decide how to handle results, interruptions, or revised goals.
Helps a QwenPaw Worker choose between direct work, short parallel checks, and temporary agents with custom roles. It guides dependent task execution, shared files, progress updates, result merging, and removal of temporary agents after the work ends.
Retrieve shared reference files and send work in progress using local shared paths. The skill also guides missing-file checks and distinguishes manual file transfers from synchronization already handled by task acceptance and submission.
Manage an AI team's project plans and recorded progress, including task dependencies and repeated improvement cycles. Track accepted results, identify work ready to start, pause or resume projects, and prepare status reports for requesters.
Guides communication in Matrix agent teams by choosing recipients, rooms, and when to mention someone. It covers task notifications and progress reports, helping agents avoid duplicate assignments and send concrete updates to the appropriate requester.
Handle standalone administration tasks on a Tuwunel Matrix server, including registering users, creating rooms, managing membership, and uploading files. It also covers sending files to an administrator and identifies mention and room-joining requirements that affect Workers.
Call tools on configured MCP servers, which connect agents to external services, through the mcporter CLI. Inspect available tools and their inputs, retrieve API information, and check connections before deciding how to proceed.
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