rhdh-jira

name	rhdh-jira
description	Interacts with RHDH Jira projects (RHIDP, RHDHPLAN, RHDHBUGS, RHDHSUPP) using acli, GraphQL, and REST API. Covers the full Jira lifecycle: create issues, assign, refine, plan sprints, report, track releases, and update status. Trigger on Jira keys (RHIDP-1234), "create a feature/epic/story/task/bug", "who should take this", "refine this", "plan the sprint", "sprint report", "release status", "update jira", or any sprint ceremony prep.
compatibility	acli (Atlassian CLI) on PATH. Python 3 for scripts. Windows, macOS, Linux.

RHDH Jira

Foundational skill for interacting with RHDH's Jira instance via the Atlassian CLI (acli). Covers all four active projects, issue types, workflows, custom fields, and JQL patterns.

Commands

Command	Description	Reference
assign [issue key(s) or JQL]	Recommend and assign team members using expertise, capacity, and context proximity analysis	references/assign.md
refine [issue key(s), JQL, or 'sprint']	Check issues against exit criteria, identify duplicates, missing fields, unaddressed comments, and readiness	references/refine.md
plan [team]	Sprint planning prep: carryover, velocity, capacity, ready queue, sprint fill suggestions	references/plan.md
sprint-report [team]	Sprint review summary: committed vs completed, per-member breakdown, demo checklist	references/sprint-report.md
release [version]	Release readiness: feature matrix, PI funnel, dependency map, blocker bugs, risk assessment	references/release.md
to-feature [description]	Create a RHDHPLAN Feature with grill, duplicate check, and optional Epic decomposition	references/to-feature.md
to-epic [description]	Create an RHIDP Epic with grill, duplicate check, and optional Story/Task decomposition	references/to-epic.md
to-issue [description]	Create a Story, Task, Bug, or Spike with automatic type inference and grill	references/to-issue.md
update-jira-status [key]	Update issue with session progress, status comment, transition, and upward cascade	references/update-jira-status.md

Single source of truth for command descriptions: scripts/command-metadata.json

Routing rules

1. No argument: Show the command menu. Ask what to do.
2. First word matches a command: Load its reference file and follow it.
3. First word doesn't match: General Jira invocation using the full argument as context — use the reference files table below to decide what to load.

Prerequisites

Run scripts/setup.py to verify everything is configured:

python scripts/setup.py

The script checks:

1. acli binary on PATH
2. Jira API token auth configured (~/.config/acli/jira_config.yaml)
3. .jira-token file next to acli executable (for REST API fallback)
4. Smoke test against redhat.atlassian.net

If acli is not installed, download from Atlassian CLI and follow the Getting Started guide for installation and authentication setup. Use API token authentication, not OAuth — OAuth sessions expire and acli auth status gives false negatives with token auth (see Gotchas).

API preference order

All operations follow this priority: acli → GraphQL → REST API.

• acli — default for simple, single-issue operations (view, edit, assign, transition).
• GraphQL — for bulk reads where acli would be too slow (expertise profiles, capacity, refinement checks). Skip acli entirely for bulk.
• REST API — for writes when already in an authenticated API context (avoids shelling out to acli mid-workflow), or as fallback when acli fails for custom field updates.

Sub-commands (assign, refine) document which API they use. When a sub-command's workflow already has AUTH set from GraphQL reads, prefer REST for writes.

REST/GraphQL capability gate

Before attempting any REST API or GraphQL call:

1. Run python scripts/setup.py --json and check token_file_found
2. If missing, state: "REST API/GraphQL fallback unavailable — .jira-token not configured. Run setup.py for instructions." Continue with acli-only workflow.
3. If the user needs REST/GraphQL, load references/auth.md for setup instructions

Scripts

Script	Purpose
scripts/setup.py	Verify acli install + auth. Run with --json for structured output.
scripts/parse_issues.py	Flatten, enrich, and filter acli JSON output. Solves the core problem: acli search --json can't return custom fields (team, story points, sprint). Pipe search results in, get clean data out. Use --enrich to fetch full fields, -f team="X" to filter by team.
scripts/command-metadata.json	Single source of truth for sub-command descriptions and argument hints.

Projects

Key	Purpose	Issue Types
RHIDP	Engineering work	Epic, Story, Task, Sub-task, Vulnerability
RHDHPLAN	Program planning	Feature, Outcome, Feature Request, Sub-task
RHDHBUGS	Product defects	Bug, Sub-task
RHDHSUPP	Support-engineering interactions	Bug

RHDHPAI (Plugins and AI) is archived — JQL queries against it will fail.

Issue type selection

• Story — end-user facing work (API, UI changes)
• Task — not end-user facing (tests, CI/CD, refactoring, code organization)
• Epic — collection of Stories/Tasks toward a deliverable
• Feature — program-level planning item in RHDHPLAN
• Bug — product defect (RHDHBUGS) or support case tracking (RHDHSUPP)
• Sub-task — child of any issue type above
• Vulnerability — CVE tracking in RHIDP (Product Security)

Reference Files

Load only what the current task requires.

File	Load when...
references/acli-commands.md	Running an acli command you haven't used before, or hitting unexpected flag behavior. Quick reference for syntax, flag differences, and output formats.
references/fields.md	Need to know a field name, custom field ID, accepted values, or label conventions. Custom fields, labels, link types, components, priorities.
references/workflows.md	Transitioning issues, checking exit criteria, or verifying readiness for the next status.
references/templates.md	Creating new issues. Also load references/workflows.md for required fields at entry status.
references/support.md	Handling support cases, filing bugs from customer cases, or creating feature requests from support.
references/jql-patterns.md	Building a JQL query, finding a board ID, or looking up sprint information. JQL cookbook with 23+ tested queries.
references/auth.md	Setting up authentication for REST API or GraphQL calls. Token file format, path discovery, security, instance config, common auth errors.
references/rest-api-fallback.md	acli failed to update a custom field (Team, Size, Story Points, Release Note Type). Curl examples, response handling, OpenAPI spec discovery.
references/graphql-queries.md	Complex read queries needing multiple fields, relationships, or custom field data in one call. Schema introspection, JQL search via GraphQL, field type fragments. Also for bulk operations where acli would be too slow.
references/assign.md	Recommending assignees for unassigned issues. Team roster lookup, expertise profiling, sprint capacity analysis, context proximity scoring. Also for applying assignments after user confirmation.
references/refine.md	Checking issues against exit criteria per status, identifying duplicates, missing fields, unaddressed comments, and readiness for the next workflow status.
references/plan.md	Sprint planning prep: carryover report, velocity trend, per-member capacity, ready-for-planning queue, sprint fill suggestions.
references/sprint-report.md	Sprint review summary: committed vs completed, per-member breakdown, epic progress, demo checklist with naming conventions, velocity trend.
references/release.md	Release readiness report: feature matrix, PI funnel states, epic roll-up, cross-team dependency map, blocker bugs, RN readiness, risk assessment.
references/to-feature.md	Create a RHDHPLAN Feature from conversation context with grill and optional Epic decomposition.
references/to-epic.md	Create an RHIDP Epic from conversation context with grill and optional Story/Task decomposition.
references/to-issue.md	Create a Story, Task, Bug, or Spike with automatic type inference and grill.
references/update-jira-status.md	Update a Jira issue with session progress, status comment, transitions, and upward cascade to parent Epic/Feature.
references/duplicates.md	Duplicate detection for pre-creation checks and refinement audits. Shared across creation commands and refine.
references/grill.md	Shared challenging behavior for issue creation grills: sizing, completeness, scope, risks, cross-referencing.
references/sizing.md	T-shirt sizing guide for Features/Epics and Fibonacci story points for Stories/Tasks. Used during grills and refinement.

Common Gotchas

1. acli auth status lies. It checks OAuth, not API token auth. Always returns "unauthorized" with token auth even when Jira works fine. Use acli jira project list --recent 1 as a smoke test instead.
2. view uses positional arg, everything else uses --key. acli jira workitem view RHIDP-123 but acli jira workitem edit --key RHIDP-123 ....
3. --yes is mandatory for mutations. All edit, transition, assign, and link create commands prompt interactively without it. Always pass --yes.
4. --fields is restrictive on search. Only accepts key, summary, status, assignee, issuetype, priority, description, labels. For components, sprint, fixVersions, and all custom fields — use --json or scripts/parse_issues.py --enrich.
5. Team field has two JQL syntaxes. customfield_10001 cannot be used in JQL WHERE clauses. However, "Team[Team]" = {teamId} (using the team UUID, not display name) works. Use the UUID syntax for JQL filtering; use customfield_10001.name in post-processing only when you need the display name from JSON output.
6. ADF vs plain text. Reading descriptions via --json returns Atlassian Document Format (nested JSON). Creating/editing with --description accepts plain text. Don't try to round-trip ADF through --description.
7. Acceptance Criteria field is almost always null. Scan the description for "Requirements", "Acceptance Criteria", or bullet-style criteria instead of checking customfield_10718.
8. --enrich is MANDATORY for custom fields. Both acli search --json and acli view KEY --json (without --fields "*all") return only basic fields (assignee, issuetype, priority, status, summary). Story points, team, sprint, and size will appear as empty/null — looking like the data isn't set when it actually is. Always use scripts/parse_issues.py --enrich to get custom field data. Skipping --enrich is the #1 cause of false "missing data" reports.
9. Custom fields may fail to update via acli. acli jira workitem edit can silently fail or error when setting custom fields (Team, Size, Story Points). When an acli edit for a custom field fails, fall back to the Jira REST API. Find the token file at .jira-token next to the acli executable (discover the path with readlink -f "$(which acli)" or where acli). Read references/rest-api-fallback.md for curl examples and payload formats. Never read the token file into context.
10. acli sprint list-workitems --json wraps results in {"issues": [...]}. The output is NOT a flat array — it's an object with an issues key. Extract the array before piping to parse_issues.py. See references/acli-commands.md for the workaround command.
11. GraphQL search is beta. issueSearchStable requires X-ExperimentalApi: JiraIssueSearch header. Load references/graphql-queries.md before attempting GraphQL queries.
12. .jira-token format is email:token, not bare token. A file containing only the API token without the email prefix will cause 401 errors on REST/GraphQL calls. The setup.py script validates the format.

Error Handling

Error	Action
acli not on PATH	Run scripts/setup.py. Install from Atlassian if missing. See Getting Started.
"unauthorized" from auth status	Ignore. Check jira_config.yaml exists. Run smoke test.
"required flag(s) not set"	Command syntax wrong. Run acli jira <subcommand> --help.
"field X is not allowed"	Use --json instead of --fields for that field.
"the value X does not exist for the field 'project'"	Project key is wrong or project is archived (e.g., RHDHPAI).
Rate limiting (429)	Wait 5 seconds, retry once.
Interactive prompt hangs	Missing --yes flag on a mutating command.
Custom field update fails via acli	Fall back to Jira REST API using .jira-token file. See Gotcha #9.
issueSearchStable returns errors	Fall back to REST API search (/rest/api/3/search) with the same JQL. Warn that the beta API failed.

Team Conventions

These apply across all sub-commands:

• Release Pending counts as completed. Release Pending items remain in the sprint and count toward velocity and capacity. They represent done work awaiting release.
• Confirmation flow. Sub-commands that modify Jira issues use a standard prompt: "Apply changes? [y/N/edit]" — y applies all, N cancels, edit steps through each change individually.
• Closure requires rationale. When closing or descoping issues, always add a comment documenting the reason and set the resolution field (Won't Do, Duplicate, Done). Preserves the decision trail.
• Comments over description bloat. Issue descriptions use the structured template sections. Decision trail, elaboration, abandoned approaches, and customer context go in comments. Creation commands proactively suggest comments for context that emerged during the grill.

Common Workflows

Sub-commands share data. plan reuses roster/capacity/expertise from assign. sprint-report uses the same velocity query pattern as plan. release references exit criteria from workflows.md and can invoke assign for unassigned Features.

Creating an issue

1. Load references/templates.md for the body template
2. Load references/workflows.md for required fields at New status
3. Run acli jira workitem create (see references/acli-commands.md if unsure of syntax)

Searching with custom fields (team, story points, sprint)

1. Build JQL using patterns from references/jql-patterns.md
2. Pipe results through scripts/parse_issues.py --enrich for full field data
3. Use -f team="X" to filter by team (not possible in JQL)

Transitioning an issue

1. Load references/workflows.md for exit criteria at the target status
2. Verify required fields are set before transitioning
3. Run acli jira workitem transition --key KEY --status "X" --yes

Complex queries (many fields, relationships)

1. Load references/graphql-queries.md
2. Use issueByKey for single issues or issueSearchStable (beta) for JQL search
3. Fall back to acli + parse_issues.py --enrich if GraphQL returns errors

Recommending and assigning issues

1. Load references/assign.md
2. Identify unassigned issues (single key, JQL query, or passed-in list)
3. Determine the team (from issue field, parent epic, or user input)
4. Run deep or quick analysis per the reference
5. Present recommendations, get user confirmation, then assign

Refining issues

1. Load references/refine.md
2. Identify issues to refine (specific keys, JQL, sprint, or backlog)
3. Run all 6 checks: missing fields, duplicates, hierarchy, comments, staleness, sprint readiness
4. Present refinement report with actionable recommendations
5. Optionally apply auto-fixable changes and prompt for manual decisions

Sprint planning prep

1. Load references/plan.md
2. Resolve team, board, and sprint context
3. Generate carryover report, velocity trend, capacity snapshot, and ready-for-planning queue
4. Auto-generate sprint fill suggestions with expertise matching
5. Surface critical customer bugs (exempt from capacity) and retro action items

Sprint review summary

1. Load references/sprint-report.md
2. Resolve sprint (active or previous)
3. Partition completed vs carried over, compute completion rate
4. Per-member breakdown, epic progress, demo checklist with naming conventions
5. Optionally save as markdown file

Release readiness

1. Load references/release.md
2. Fetch Features for the target version/label
3. Quick mode: PI funnel, feature matrix, readiness score
4. Deep mode: adds epic roll-up, dependency map, coherence analysis, RN readiness, risk assessment
5. Optionally remediate (assign owners, create Epics, transition statuses)

Creating Features, Epics, and Issues

1. Load the appropriate creation reference (to-feature.md, to-epic.md, or to-issue.md)
2. Load references/grill.md for challenging behavior
3. Load the template + example pair from assets/templates/ and assets/examples/
4. Grill the user on scope, AC, sizing (reference references/sizing.md)
5. Run duplicate check per references/duplicates.md
6. Create the issue, suggest comments for decision trail
7. Offer chained decomposition (Feature → Epics → Stories/Tasks)

Updating Jira from a session

1. Load references/update-jira-status.md
2. Detect related issue (conversation → git → PR → commits → keyword search)
3. Compose status comment, propose transition
4. Check upward cascade (sibling completion → parent transition)
5. Suggest reaching out to Feature Owner if Feature-level work is complete

Discovering unknown fields or endpoints

1. For REST: load references/rest-api-fallback.md — use the OpenAPI spec or /rest/api/3/field endpoint
2. For GraphQL: load references/graphql-queries.md — use __type introspection queries
3. Do not guess field IDs or types — always verify against the live schema

When NOT to Use

• Non-RHDH Jira projects — this skill's field mappings, workflows, and JQL patterns are specific to RHIDP/RHDHPLAN/RHDHBUGS/RHDHSUPP
• Jira REST API directly — use acli first, then GraphQL for bulk reads. REST API is the last resort for writes when acli fails and for schema discovery via OpenAPI spec (see Gotcha #9)
• GraphQL for simple lookups — use acli for single-issue views and simple searches. GraphQL is for bulk operations, complex queries needing relationships or many custom fields in one call, team roster lookups, and schema introspection