github-triage
Triage GitHub issues through a label-based state machine with interactive grilling sessions. Use when user wants to triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.
What this skill does
# GitHub Issue Triage Triage issues in the current repo using a label-based state machine. Infer the repo from `git remote`. Use `gh` for all GitHub operations. ## AI Disclaimer Every comment or issue posted to GitHub during triage **must** include the following disclaimer at the top of the comment body, before any other content: ``` > *This was generated by AI during triage.* ``` ## Reference docs - [AGENT-BRIEF.md](AGENT-BRIEF.md) — how to write durable agent briefs - [OUT-OF-SCOPE.md](OUT-OF-SCOPE.md) — how the `.out-of-scope/` knowledge base works ## Labels | Label | Type | Description | | ----------------- | -------- | ---------------------------------------- | | `bug` | Category | Something is broken | | `enhancement` | Category | New feature or improvement | | `needs-triage` | State | Maintainer needs to evaluate this issue | | `needs-info` | State | Waiting on reporter for more information | | `ready-for-agent` | State | Fully specified, ready for AFK agent | | `ready-for-human` | State | Requires human implementation | | `wontfix` | State | Will not be actioned | Every issue should have exactly **one** state label and **one** category label. If an issue has conflicting state labels (e.g. both `needs-triage` and `ready-for-agent`), flag the conflict and ask the maintainer which state is correct before doing anything else. Provide a recommendation. ## State Machine | Current State | Can transition to | Who triggers it | What happens | | -------------- | ----------------- | ---------------------- | -------------------------------------------------------------------------------------------------------------------- | | `unlabeled` | `needs-triage` | Skill (on first look) | Issue needs maintainer evaluation. Skill applies label after presenting recommendation. | | `unlabeled` | `ready-for-agent` | Maintainer (via skill) | Issue is already well-specified and agent-suitable. Skill writes agent brief comment, applies label. | | `unlabeled` | `ready-for-human` | Maintainer (via skill) | Issue requires human implementation. Skill writes a brief comment summarizing the task, applies label. | | `unlabeled` | `wontfix` | Maintainer (via skill) | Issue is spam, duplicate, or out of scope. Skill closes with comment (and writes `.out-of-scope/` for enhancements). | | `needs-triage` | `needs-info` | Maintainer (via skill) | Issue is underspecified. Skill posts triage notes capturing progress so far + questions for reporter. | | `needs-triage` | `ready-for-agent` | Maintainer (via skill) | Grilling session complete, agent-suitable. Skill writes agent brief comment, applies label. | | `needs-triage` | `ready-for-human` | Maintainer (via skill) | Grilling session complete, needs human. Skill writes a brief comment summarizing the task, applies label. | | `needs-triage` | `wontfix` | Maintainer (via skill) | Maintainer decides not to action. Skill closes with comment (and writes `.out-of-scope/` for enhancements). | | `needs-info` | `needs-triage` | Skill (detects reply) | Reporter has replied. Skill surfaces to maintainer for re-evaluation. | An issue can only move along these transitions. The maintainer can override any state directly (see Quick State Override below), but the skill should flag if the transition is unusual. ## Invocation The maintainer invokes `/github-triage` then describes what they want in natural language. The skill interprets the request and takes the appropriate action. Example requests: - "Show me anything that needs my attention" - "Let's look at #42" - "Move #42 to ready-for-agent" - "What's ready for agents to pick up?" - "Are there any unlabeled issues?" ## Workflow: Show What Needs Attention When the maintainer asks for an overview, query GitHub and present a summary grouped into three buckets: 1. **Unlabeled issues** — new, no labels at all. These have never been triaged. 2. **`needs-triage` issues** — maintainer needs to evaluate or continue evaluating. 3. **`needs-info` issues with new activity** — the reporter has commented since the last triage notes comment. Check comment timestamps to determine this. Display counts per group. Within each group, show issues oldest first (longest-waiting gets attention first). For each issue, show: number, title, age, and a one-line summary of the issue body. Let the maintainer pick which issue to dive into. ## Workflow: Triage a Specific Issue ### Step 1: Gather context Before presenting anything to the maintainer: - Read the full issue: body, all comments, all labels, who reported it, when - If there are prior triage notes comments (from previous sessions), parse them to understand what has already been established - Explore the codebase to build context — understand the domain, relevant interfaces, and existing behavior related to the issue - Read `.out-of-scope/*.md` files and check if this issue matches or is similar to a previously rejected concept ### Step 2: Present a recommendation Tell the maintainer: - **Category recommendation:** bug or enhancement, with reasoning - **State recommendation:** where this issue should go, with reasoning - If it matches a prior out-of-scope rejection, surface that: "This is similar to `.out-of-scope/concept-name.md` — we rejected this before because X. Do you still feel the same way?" - A brief summary of what you found in the codebase that's relevant Then wait for the maintainer's direction. They may: - Agree and ask you to apply labels → do it - Want to flesh it out → start a grilling session - Override with a different state → apply their choice - Want to discuss → have a conversation ### Step 3: Bug reproduction (bugs only) If the issue is categorized as a bug, attempt to reproduce it before starting a grilling session. This will vary by codebase, but do your best: - Read the reporter's reproduction steps (if provided) - Explore the codebase to understand the relevant code paths - Try to reproduce the bug: run tests, execute commands, or trace the logic to confirm the reported behavior - If reproduction succeeds, report what you found to the maintainer — include the specific behavior you observed and where in the code it originates - If reproduction fails, report that too — the bug may be environment-specific, already fixed, or the report may be inaccurate - If the report lacks enough detail to attempt reproduction, note that — this is a strong signal the issue should move to `needs-info` The reproduction attempt informs the grilling session and the agent brief. A confirmed reproduction with a known code path makes for a much stronger brief. ### Step 4: Grilling session (if needed) If the issue needs to be fleshed out before it's ready for an agent, interview the maintainer to build a complete specification. ### Step 5: Apply the outcome Depending on the outcome: - **ready-for-agent** — post an agent brief comment (see [AGENT-BRIEF.md](AGENT-BRIEF.md)) - **ready-for-human** — post a comment summarizing the task, what was established during triage, and why it needs human implementation. Use the same structure as an agent brief but note the reason it can't be delegated to an agent (e.g. requires judgment calls, external system access, design decisions, or manual testing). - **needs-info** — post triage notes with progress so far and questions for the reporter (see Needs Info Output below) - **wontfix (bug)** — post a polite comment explaining why, then close the issue - **wontfix (enhancement)** — write to `.out-of-scope/`, post a comme
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.