setup
Installe les outils CLI prérequis (gh, glab, jq), guide l'authentification GitHub/GitLab, installe uvx et configure le serveur MCP mcp-atlassian pour Jira dans OpenCode. Idempotent : relancer le skill est sans danger. Déclenché quand l'utilisateur dit « setup », « install prerequisites » ou « configurer jira ».
What this skill does
# Setup — Prerequisites & MCP Configuration
Install CLI tools, authenticate to GitHub/GitLab, and configure the `mcp-atlassian` Jira integration for OpenCode.
## Prerequisites
- Linux with `apt` package manager
- `bash` and `curl` available
- Internet access (for apt packages and uv installer)
## Trigger
User says: "setup", "install prerequisites", "configure jira", or similar.
> **Important — interactive skill only.** This skill requires user interaction (auth prompts, Jira credentials). It must **not** be called as a sub-step from autonomous skill pipelines (fast-meeting, issue-review, etc.) — doing so will stall the pipeline waiting for input that will never arrive.
---
## Workflow
### Phase 1 — Install CLI tools
Run the bundled script to install missing tools (idempotent — skips already-installed ones):
```bash
bash "$(dirname "$0")/reference/setup.sh"
```
The script installs (via `apt` if not already present):
- `gh` — GitHub CLI
- `glab` — GitLab CLI
- `jq` — JSON processor
- `uvx` — via the official `uv` installer (`curl -LsSf https://astral.sh/uv/install.sh | sh`)
After running, inform the user of what was installed vs. already present.
### Phase 2 — CLI Authentication
Check and authenticate each CLI:
```bash
gh auth status 2>&1
```
- Show the full output to the user (current logged-in account, token scopes, etc.)
- If not authenticated → tell the user: "Run `gh auth login` and follow the prompts."
- Do NOT run `gh auth login` automatically (requires interactive input).
```bash
glab auth status 2>&1
```
- Show the full output to the user (GitLab instance, current user, token validity, etc.)
- If not authenticated → tell the user: "Run `glab auth login` and follow the prompts."
- Do NOT run `glab auth login` automatically.
### Phase 3 — Configure mcp-atlassian for Jira
**Step 3.1 — Check if uvx is available:**
```bash
uvx --version 2>&1 || ~/.local/bin/uvx --version 2>&1
```
If not found, remind the user to restart their shell or source `~/.bashrc` / `~/.profile` after the Phase 1 script ran.
**Step 3.2 — Read existing OpenCode config:**
Use the Read tool to read `~/.config/opencode/opencode.json`.
- If the file does not exist, treat it as `{}`.
- If `mcp.mcp-atlassian` is already present → confirm to the user and skip the rest of Phase 3.
**Step 3.3 — Gather credentials (if not already configured):**
Ask the user these two questions in a single message:
1. **Jira URL** — default `https://jira.dedalus.com/` (Server/Data Center). Press Enter to accept.
2. **Jira Personal Access Token (PAT)** — steps to generate one:
- Log in to your Jira instance
- Go to **Profile → Personal Access Tokens**
- Click **Create token**, give it a name, set an expiry
- Copy the token and paste it here
> For **Jira Cloud** users: use `JIRA_USERNAME` (your email) + `JIRA_API_TOKEN` (from https://id.atlassian.com/manage-profile/security/api-tokens) instead of a PAT.
**Step 3.4 — Write the config:**
Merge the `mcp-atlassian` block into `~/.config/opencode/opencode.json`, preserving any existing content. Use the Write tool to write the final JSON.
For **Server/Data Center** (default):
```json
{
"mcp": {
"mcp-atlassian": {
"type": "local",
"command": ["uvx", "mcp-atlassian"],
"environment": {
"JIRA_URL": "<jira-url>",
"JIRA_PERSONAL_TOKEN": "<pat>"
},
"enabled": true
}
}
}
```
For **Cloud** (if user specifies):
```json
{
"mcp": {
"mcp-atlassian": {
"type": "local",
"command": ["uvx", "mcp-atlassian"],
"environment": {
"JIRA_URL": "<jira-url>",
"JIRA_USERNAME": "<email>",
"JIRA_API_TOKEN": "<api-token>"
},
"enabled": true
}
}
}
```
**Step 3.5 — Secure the config file:**
```bash
chmod 600 ~/.config/opencode/opencode.json
```
### Phase 4 — Summary
Print a clear summary table:
| Component | Status |
|-----------|--------|
| gh | installed / already ok |
| glab | installed / already ok |
| jq | installed / already ok |
| uvx | installed / already ok |
| gh auth | authenticated / action needed |
| glab auth | authenticated / action needed |
| mcp-atlassian | configured / already ok / skipped |
End with: "Restart OpenCode to load the new MCP configuration."
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.