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/fix-issue

Fixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the resolution back to the issue

From plugin
orchestkit
269113 skills36 agents
Install
$ npx -y skills add yonatangross/orchestkit --skill fix-issue --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/fix-issue

Context preview

The summary Claude sees to decide when to auto-load this skill.

Fixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the resolution back to the issue

SKILL.md

fix-issue.SKILL.md
name: fix-issue
license: MIT
compatibility: "Claude Code 2.1.251+. Requires memory MCP server, context7 MCP server, gh CLI."
description: "Fixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the resolution back to the issue via PR. Includes prevention analysis to avoid recurrence. Use when debugging errors, resolving regressions, fixing bugs, or triaging issues."
argument-hint: "[issue-number]"
context: fork
# user-typed commands stay interactive; CC >= 2.1.218 backgrounds forks by default (#3093)
background: false
version: 2.6.0
author: OrchestKit
tags: [issue, bug-fix, github, debugging, rca, prevention]
user-invocable: true
allowed-tools: [SendMessage, AskUserQuestion, Bash, Read, Write, Edit, Agent, TaskCreate, TaskUpdate, TaskStop, Grep, Glob, ToolSearch, ExitWorktree, CronCreate, CronDelete, PushNotification, mcp__memory__search_nodes, mcp__context7__resolve-library-id, mcp__context7__query-docs]
skills: [explore, verify, memory, remember, chain-patterns]
complexity: medium
persuasion-type: guidance
model: sonnet
hooks:
  PreToolUse:
    - matcher: "Read"
      command: "${CLAUDE_PLUGIN_ROOT}/hooks/bin/run-hook.mjs skill/issue-context-loader"
      once: true
metadata:
  category: workflow-automation
  mcp-server: memory, context7
triggers:
  keywords: [fix, debug, "bug report", broken, "500 errors", investigate, resolve, regression, "track down", "figure out why", "issue #"]
  examples:
    - "fix issue #234"
    - "there's a bug where users can't reset their passwords"
    - "something's causing 500 errors on the /api/users endpoint"
  anti-triggers: [implement, build, create, explore, review, brainstorm]
paths: ["src/**/*.{ts,tsx,js,jsx}", "package.json", "CLAUDE.md"]

Fix Issue

Host-neutral workflow. Invoke by skill name (`fix-issue`). Claude Code slash routing, YAML hook loaders, and `.claude/chain` live in `references/claude-code.md`.

Systematic issue resolution with hypothesis-based root cause analysis, similar issue detection, and prevention recommendations.

Quick Start

fix-issue 123
fix-issue 456

> **Opus 5**: Root cause analysis uses native adaptive thinking. Dynamic token budgets scale with context window for thorough investigation.

> **CC ≥ 2.1.119 multi-host note (M122):** Issue fetching works against GitHub, GitLab, Bitbucket, and GitHub Enterprise. The argument is either a numeric ID (use the configured default remote's host) or a full URL (parsed via `parsePrUrl`/`parseIssueUrl` from `src/hooks/src/lib/pr-host-parser.ts`). Branch on the detected host family for the right CLI: `gh issue view` (GitHub/GHE), `glab issue view` (GitLab), `bb issue view` (Bitbucket). Reference: `src/skills/chain-patterns/references/pr-from-platform.md`.

Argument Resolution

ISSUE_NUMBER = "$ARGUMENTS[0]"  # e.g., "123" (CC 2.1.59 indexed access)
# $ARGUMENTS contains the full argument string
# $ARGUMENTS[0] is the first space-separated token

STEP -1: MCP Probe + Resume Check

**Run BEFORE any other step.** Detect available MCP servers and check for resumable state.

# Probe MCPs (parallel — all in ONE message):
# memory is alwaysLoad in .mcp.json (CC 2.1.121+, #1541) — probe below kept as fallback for older CC:
ToolSearch(query="select:mcp__memory__search_nodes")
ToolSearch(query="select:mcp__context7__resolve-library-id")

# Write capability map:
Write(".claude/chain/capabilities.json", JSON.stringify({
  "memory": <true if found>,
  "context7": <true if found>,
  "timestamp": now()
}))

# Check for resumable state:
Read(".claude/chain/state.json")
# If exists and skill == "fix-issue":
#   Read last handoff, skip to current_phase
#   Tell user: "Resuming from Phase {N}"
# If not exists: write initial state
Write(".claude/chain/state.json", JSON.stringify({
  "skill": "fix-issue",
  "issue": ISSUE_NUMBER,
  "current_phase": 1,
  "completed_phases": [],
  "capabilities": capabilities
}))

> Load pattern details: `Read("../chain-patterns/references/mcp-detection.md")`

Phase 0b — Prior-fix lookup (signal-fired, optional)

Before diagnosis kicks off, optionally invoke `scripts/prior_fix_lookup.py <session-dir>` to surface similar fixes already recorded in the memory MCP. READ-ONLY — no writeback. Self-skips on every non-happy-path so it never blocks the fix:

python3 ${CLAUDE_SKILL_DIR}/scripts/prior_fix_lookup.py "$CLAUDE_JOB_DIR"

Auto-skip conditions (all exit 0, all WARN-logged):

| Skip reason | Trigger | |-------------|---------| | `signal absent` | `error_text` missing OR signature extractor returns `None` | | `yg-mcp-core not importable` | `yg-mcp-core>=0.3.0` not installed (orchestkit is public; yg-mcp-core lives on private `pypi.yonyon.ai` — HQ-only) | | `memory MCP unreachable` | MCP server down OR `.mcp.json` doesn't define `memory` |

Session dir must contain `fix-issue-input.json` (with `error_text: str`). The signature extractor (`signature_lib.extract_signature`) normalizes Python tracebacks, JS stack traces, and generic `<Type>: <msg>` errors to a `<error_type> <primary_path>:<lineno>` shape used as the `search_nodes` query. Handoff JSON at `<session-dir>/prior-fix-matches.json` records `status`, `signature`, and `matches_count`; the top-3 matches land in `<session-dir>/prior-fix-matches.md` as a Markdown table.

Mirrors the memory-consumer pattern from PR #1889 but read-only. Closes orchestkit#1895.

CRITICAL: Task Management is MANDATORY (CC 2.1.16)

**BEFORE doing ANYTHING else (after MCP probe), create tasks to track progress:**

# 1. Create main task IMMEDIATELY
TaskCreate(
  subject="Fix Issue: #{ISSUE_NUMBER}",
  description="Systematic issue resolution with RCA and prevention",
  activeForm="Fixing issue #{ISSUE_NUMBER}"
)

# 2. Create subtasks for each key phase
TaskCreate(subject=
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