claude

agent-authoring

Skills for authoring AGENTS.md project-context files, SKILL.md agent skills, GitHub Copilot CLI custom agents, Claude Code custom subagents, compact and executable agent-facing Markdown, graph-pattern multi-agent squads/swarms, choosing which AI model an agent should use, building apps with the GitHub Copilot SDK, automating Copilot CLI in GitHub Actions, converting data to/from TOON (Token-Oriented Object Notation) to cut LLM token usage, authoring Mermaid diagrams in markdown files, following general Markdown formatting best practices, searching files and code with ripgrep, producing and consuming Open Knowledge Format bundles, creating polished Python terminal interfaces and skill scripts with Textual and Rich, and finding, querying, and troubleshooting logs, transcripts, and OpenTelemetry traces from coding-agent harnesses.

2 on GitHubv0.15.1MITupdated 6 days ago
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Plugin agent-authoring from marketplace intelligentium in NetFabric/intelligentium. Commands read from the repo's manifest — 6 days ago.

What it installs

Skills (16)

  • agent-graph-orchestration

    Design and scaffold multi-agent squads/swarms using the graph orchestration pattern (nodes = agents, edges = dependencies/data flow). USE FOR: designing a coordination topology for a multi-agent squad (sequential pipeline, parallel fan-out/aggregation, branching, feedback loop, cyclic); building an

  • agent-harness-logs

    Find, inspect, query, redact, and troubleshoot logs, transcripts, sessions, and OpenTelemetry data from coding-agent harnesses on Windows, macOS, Linux, and WSL. USE FOR: GitHub Copilot in VS Code; Copilot CLI; Claude Code; OpenAI Codex; Gemini CLI; OpenCode; Cursor, Windsurf, Kiro, or other VS Code

  • agent-markdown-best-practices

    ALWAYS use when writing or reviewing agent-facing Markdown, including project instructions, skills and references, and custom-agent definitions. Covers only their shared content style: compact executable instructions, scannable information, active language, factual precision, and token efficiency. D

  • agents-md

    Author and maintain AGENTS.md files — the open, tool-agnostic format for giving coding agents project context. Use when: creating AGENTS.md; writing an agent instructions file; root or nested AGENTS.md for monorepos; migrating CLAUDE.md, AGENT.md, .cursor/rules, or copilot-instructions.md to AGENTS.

  • claude-code-custom-agents

    Create and maintain Claude Code custom subagents (.claude/agents/*.md files). USE FOR: authoring project (.claude/agents/) or user (~/.claude/agents/) subagent files; frontmatter fields (name, description, tools, disallowedTools, model, permissionMode, maxTurns, skills, mcpServers, hooks, memory, ba

  • copilot-cli-custom-agents

    Create and maintain GitHub Copilot CLI custom agents (.agent.md files). USE FOR: authoring .github/agents or ~/.copilot/agents profiles; frontmatter fields (description, target, name, model, tools, mcp-servers, disable-model-invocation, user-invocable, deferred-tool-loading, skills, reasoning-effort

  • copilot-github-actions

    Automate GitHub Copilot CLI in GitHub Actions workflows. USE FOR: installing/running `copilot -p` in workflow steps, choosing GITHUB_TOKEN vs a personal access token (COPILOT_GITHUB_TOKEN) for authentication, setting the copilot-requests write permission, minimal-permission tool allowlisting (--allo

  • copilot-sdk

    Embed the GitHub Copilot agent runtime into your own application using the Copilot SDK. USE FOR: CopilotClient/createSession setup, streaming responses, custom tools, permission handlers, hooks (pre/post-tool-use, session-start), custom agents and sub-agent delegation, MCP servers, skill and plugin

  • create-skill

    Create or update AI agent skills (SKILL.md + reference files) for any harness that supports the format: GitHub Copilot, Claude Code, Cursor, Codex, Gemini CLI, Windsurf, Kiro, OpenCode, and more. Use when: authoring a new skill from scratch, improving or restructuring an existing skill, deciding how

  • markdown-best-practices

    ALWAYS use this skill whenever creating, editing, or reviewing any Markdown (.md) file — README.md, SKILL.md, AGENTS.md, CONTRIBUTING.md, changelogs, or any other Markdown documentation — even for small edits. Write and review Markdown files for consistent, correctly-rendering formatting: heading hi

  • mermaid-diagrams

    Author Mermaid diagrams inside ```mermaid fenced code blocks in markdown files (README, AGENTS.md, PR descriptions, chat responses). Covers every stable, non-experimental diagram type: flowchart, sequence, class, state, entity relationship, user journey, Gantt, pie, quadrant, requirement, gitGraph,

  • model-selection

    Choose and tune which AI model a custom agent, subagent, or squad node should use. USE FOR: picking a model by task capability tier (general-purpose coding/writing, fast/cheap, deep reasoning/debugging, multimodal); efficiency-first vs. capability-first starting strategies; tuning an effort/reasonin

  • okf

    Produce, consume, validate, and navigate Open Knowledge Format (OKF) bundles. Use when: creating an OKF knowledge bundle; converting catalogs, wikis, schemas, metrics, runbooks, or APIs to OKF; parsing or indexing OKF; designing an OKF producer or consumer; validating OKF v0.2 conformance; traversin

  • python-tui-apps

    Create polished Python terminal user interfaces and skill scripts with Textual and Rich. Use when: building TUI apps; adding interactive terminal workflows; designing tabs, progress bars, checkboxes, radio buttons, tables, charts, forms, status views, keyboard navigation, color, or responsive termin

  • ripgrep

    Search files and code with ripgrep (`rg`) after preferring available code-indexing tools. Use when: finding literal text or regex matches; listing searchable files; filtering by glob or file type; checking whether `rg` is installed; installing ripgrep on macOS, Linux, or Windows; replacing legacy te

  • toon

    Convert data to/from TOON (Token-Oriented Object Notation) for lower-token LLM context. Use when: encoding JSON/YAML to TOON; decoding TOON back to JSON; estimating token savings vs JSON; sending tabular data in a prompt; choosing a delimiter (comma, tab, pipe); validating model-generated TOON with

View source on GitHub intelligentium.ai

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