skills/querying-jira-programmatically/SKILL.md
Run Jira MCP searches (Rovo or JQL) via mcpc-backed Python wrappers with cached tool schemas and file-backed outputs. Use when Codex needs deterministic Jira queries using @jira and mcpc (no direct HTTP).
npx skillsauth add aufrank/agent-skills querying-jira-programmaticallyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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search and searchJiraIssuesUsingJql, with generic tool caller and cached schemas.results/ + .mcpc-skill-caches/).python <CODEX_HOME>/skills/querying-jira-programmatically/scripts/jira_search.py --query "incident backlog"python <CODEX_HOME>/skills/querying-jira-programmatically/scripts/jira_search_jql.py --jql "project = ABC ORDER BY updated DESC" --max-results 25python <CODEX_HOME>/skills/querying-jira-programmatically/scripts/jira_call_tool.py --tool search --arg query:="AI" --refresh-cacheMCPC_BIN="<TOOL_HOME>" (optional POWERSHELL_EXE).mcpc on PATH; Python 3.11+.mcpc https://mcp.atlassian.com/v1/mcp login --profile <name> (default default).@jira session, server https://mcp.atlassian.com/v1/mcp, profile from MCP_PROFILE or default.MCPC_BIN="<TOOL_HOME>"; set POWERSHELL_EXE for a specific PowerShell if needed.templates/plan.search.json or templates/plan.jql.json.jira_search.py (Rovo), jira_search_jql.py (JQL), or jira_call_tool.py (any tool).results/ and cached schemas under .mcpc-skill-caches/querying-jira-programmatically/mcp_tools/. Reuse files instead of re-running.search.--query (required), --content-type jira|confluence|all (default jira), --output (default results/jira.search.json), --session/@jira, --profile, --server. Writes payload; prints count + key/url summary when possible.searchJiraIssuesUsingJql.--jql (required), --cloud-id (default cached for this Jira instance), --max-results (default 50), --pages (follow nextPageToken), --output (default results/jira.jql.json), optional --raw-output, --no-output, --timestamp-output, --session/@jira, --profile, --server. Parses content[0].text JSON string when present; writes parsed payload (overwrites by default) and pretty-prints key/summary/status.mcp_tools/tools-list.json and mcp_tools/<tool>.json under .mcpc-skill-caches/....--tool <name> (required), repeatable --arg key:=value, --output (default results/<tool>.json), --timestamp-output, --refresh-cache, --session/@jira, --profile, --server. Warns if tool missing from cached list; always writes output JSON.tools-list), MCPC_BIN/PowerShell resolution, cache/results root detection, file writers.--project or --jql (one required), --team, --cloud-id (default set), --max-results, --output, --summary-output, optional --raw-output, --no-output, --no-summary, --timestamp-output.--project or --jql, --include-done, --cloud-id, --max-results, --output, optional --raw-output, --no-output, --timestamp-output.--project or --jql, --label (else text~"backfill"), --include-done, --cloud-id, --max-results, --output, --summary-output, optional --raw-output, --no-output, --no-summary, --timestamp-output.templates/plan.search.json: Rovo search plan scaffold (query, content_type, expected outputs).templates/plan.jql.json: JQL search plan scaffold (jql, expected outputs).references/usage.md: Quick commands, MCPC_BIN tip, cache locations..mcpc-skill-caches/querying-jira-programmatically/mcp_tools/ (tools-list + per-tool schemas). Should be gitignored; regenerate anytime.results/; caches in .mcpc-skill-caches/querying-jira-programmatically/mcp_tools/.results/*.json instead of re-calling MCP when possible.python <REPO_ROOT>/skills/creating-mcp-code-mode-skills/scripts/package_skill.py <REPO_ROOT>/skills/querying-jira-programmatically disttools
Build and execute modular DAG workflows for long-context processing using slice/map/reduce/recurse/compact/filter operators. Use for one-shot batch jobs, standalone map-reduce pipelines, or when the context-dag plugin is not installed. Trigger when input exceeds the model's context window, when reproducible logged pipelines are needed, or when multi-level recursive processing is required. If context-dag is installed, the plugin's bundled dag_runner.py provides the same capability with persistent artifact storage.
documentation
Write in Austin Frank's voice and style. Use this skill whenever generating text that should sound like Austin — strategy docs, charters, proposals, business cases, vision documents, staffing requests, stakeholder updates, cover letters, mission statements, org design documents, or any professional prose where the user wants Austin's distinctive voice. Also use when the user asks to review, edit, or improve a draft for voice consistency, or when they reference "my style", "my voice", "write like me", or "Austin's style".
tools
Use mcpc to interact with the Notion MCP server: connect sessions, search workspace content, fetch pages/databases, and run helper scripts for common Notion actions.
tools
Decide between a scripted workflow and an autonomous agent harness, then scaffold the chosen path. Use when scoping new agentic systems or tool integrations.