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Connect NanoClaw to a self-hosted or cloud Mattermost server for direct messages, channel conversations, threads, files, reactions, and approval cards. Guides server selection, bot authentication, callback configuration, and connection checks.
中文简介正在准备中。当前显示英语简介。
Set up, debug, and extend PicoClaw using its own commands and configuration structure. Get guidance on model authentication, external tool connections, scheduled tasks, and how conversations are routed and stored.
中文简介正在准备中。当前显示英语简介。
Turn pull request changes, commits, and test evidence into a self-contained HTML guide. Explain the problem, system context, before-and-after behavior, and key code changes so reviewers know where to focus.
中文简介正在准备中。当前显示英语简介。
Review an AI plan through six questions covering evaluation examples, error targets, fallback behavior, regulatory risk, model choices, costs, and hiring. Produce a structured verdict with gaps to address and three concrete next steps.
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Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.
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Close out a launched Claude Managed Agent by listing its recorded components and completed phases. Refresh a shareable, self-contained HTML overview and rank the next one or two upgrades from deferred work and operational improvements.
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Get source-backed guidance on OpenAI products, APIs, and Codex from official documentation. Use it to compare models for a task, understand configuration options, or plan focused model and prompt updates while preserving an explicitly requested target model.
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Find CAD models of off-the-shelf parts on step.parts using model names, standards, aliases, and dimensions. Compare matching records, download STEP files when needed, and check file integrity against a supplied checksum.
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Builds an Apigee proxy that inspects an agent’s model requests and responses through Google Cloud Agent Gateway. It measures token usage by model, identifies callers, and can add prompt screening or a cache for similar prompts.
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Investigate Google Cloud access denials and choose a resolution path based on the caller’s permissions. Supports temporary access activation, structured escalation tickets, policy analysis, and administrator selection of roles that grant only the permissions needed.
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Coordinate development work by breaking tasks down, writing six-part Task Prompts, and managing P8 agent teams. This skill takes a technical lead role, directing parallel agents and their delivery without writing code itself.
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Guide Trae through stalled tasks by comparing hypotheses, changing approaches after repeated failures, and checking results with relevant commands. It structures delivery around evidence, self-review, and remaining risks rather than unsupported claims of completion.
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Access the equivalent of Claude Code's /pua:pro command from Codex CLI. The alias invokes the pro protocol for self-improvement, KPI performance measures, and configuration commands, with all processing kept local.
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Guide Pi agents through repeated failures or unverified completion using competing hypotheses, small verifiable actions, and relevant checks. It separates self-review from external pass-or-fail decisions and requires evidence and remaining risks in delivery reports.
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Use past local Codex sessions to propose updates to a selected skill and project memory file. Recurring tasks are replayed, changes are checked on separate validation tasks, and proposals are staged for review before adoption.
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Review past Claude Code sessions and turn recurring tasks into proposed updates to skills and project memory. Replay tasks, compare scores on separate validation tasks, and review staged edits before applying them with backups.
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Review past dsh agent sessions to identify recurring tasks and test proposed skill or memory improvements. This skill guides preview runs, validation on reserved tasks, staged proposals, adoption with backups, and scheduled nightly cycles.
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Deploy and configure LangBot with Docker Compose or Kubernetes. Set up application settings, plugin execution, the Box sandbox for isolated commands, and API authentication, with guidance on hosting choices and common deployment problems.
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Guides iterative improvement of AI agent prompts, skills, and memory using A-Evolve. It explains how to evaluate agents against benchmark tasks, apply changes, validate results, and track or roll back revisions with Git.
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Use Phoenix to record execution traces, detailed records of an AI application's operations, and investigate problems. Evaluate answers on datasets, compare prompts and models, and set up monitoring through a self-hosted server.
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Turn vulnerability notes, proof-of-concept code, source code, or security findings into self-contained reports. The skill checks claims against evidence, explains prerequisites and demonstrated impact, and supports both individual vulnerabilities and collections of disclosure reports.
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Create a brief, polite opening when users say hello, request a self-introduction, or ask for a more formal tone. It greets first, checks the user's goal, and moves directly to any task already stated.
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Turn law study outlines, notes, or textbook excerpts into flashcards, then practice one question at a time in chat. Self-assessment updates learning stages and review dates, while subject-level statistics highlight concepts that need more work.
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Build course and workshop slides that keep learning objectives visible on the left. The deck includes concepts with examples, multiple-choice self-check questions, a wrap-up, and a preview of the next module, with warm paper tones and Playfair typography.
中文简介正在准备中。当前显示英语简介。