Link Ticket To Session
JayantDevkar/claude-code-karma
Link the current Claude Code session to a ticket (Linear, Jira, GitHub Issues, or GitHub Pull Requests) and cache its title/status in karma.
Categorize Jira issues into Red Hat Sankey Activity Type categories using MCP Jira tools.
$ npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install openshift-eng/ai-helpers categorize-activity-types --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/openshift-eng/ai-helpers.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/jira/skills/categorize-activity-types .claude/skills/categorize-activity-types && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "categorize-activity-types" agent skill from https://github.com/openshift-eng/ai-helpers/tree/main/plugins/jira/skills/categorize-activity-types into .claude/skills/categorize-activity-types/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "categorize-activity-types", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/openshift-eng/ai-helpers/tree/main/plugins/jira/skills/categorize-activity-typesType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install openshift-eng/ai-helpers categorize-activity-types --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openshift-eng/ai-helpers.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/jira/skills/categorize-activity-types .agents/skills/categorize-activity-types && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "categorize-activity-types" agent skill from https://github.com/openshift-eng/ai-helpers/tree/main/plugins/jira/skills/categorize-activity-types into .agents/skills/categorize-activity-types/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "categorize-activity-types", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install openshift-eng/ai-helpers categorize-activity-types --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openshift-eng/ai-helpers.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/jira/skills/categorize-activity-types .cursor/skills/categorize-activity-types && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "categorize-activity-types" agent skill from https://github.com/openshift-eng/ai-helpers/tree/main/plugins/jira/skills/categorize-activity-types into .cursor/skills/categorize-activity-types/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "categorize-activity-types", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/openshift-eng/ai-helpers.git --path plugins/jira/skills/categorize-activity-types--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install openshift-eng/ai-helpers categorize-activity-types --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openshift-eng/ai-helpers.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/jira/skills/categorize-activity-types .gemini/skills/categorize-activity-types && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "categorize-activity-types" agent skill from https://github.com/openshift-eng/ai-helpers/tree/main/plugins/jira/skills/categorize-activity-types into .gemini/skills/categorize-activity-types/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "categorize-activity-types", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install openshift-eng/ai-helpers categorize-activity-typesInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/openshift-eng/ai-helpers.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/jira/skills/categorize-activity-types .github/skills/categorize-activity-types && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "categorize-activity-types" agent skill from https://github.com/openshift-eng/ai-helpers/tree/main/plugins/jira/skills/categorize-activity-types into .github/skills/categorize-activity-types/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "categorize-activity-types", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install openshift-eng/ai-helpers categorize-activity-types --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openshift-eng/ai-helpers.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/jira/skills/categorize-activity-types .opencode/skills/categorize-activity-types && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "categorize-activity-types" agent skill from https://github.com/openshift-eng/ai-helpers/tree/main/plugins/jira/skills/categorize-activity-types into .opencode/skills/categorize-activity-types/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "categorize-activity-types", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
categorize-activity-typesCategorize Jira issues into Red Hat Sankey Activity Type categories using MCP Jira tools.
Categorize Activity Types is an agent skill from openshift-eng/ai-helpers. Categorize Jira issues into Red Hat Sankey Activity Type categories using MCP Jira tools. Supports single-issue and batch modes. Use when the user wants to categorize or set activity types on Jira issues, or mentions activity types, work types, Sankey, or capacity allocation.
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts (for example `resources/activity-type-guidance.md`, `resources/report-template.md` and `scripts/cleanup.sh`).
It works with Jira and Model Context Protocol. The repository describes itself as: Developer productivity tools for Claude Code & other AI assistants. The licence is Apache-2.0.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit a627176. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 3 files in scripts/ (Shell and Python), which the agent can run.
Shell commands in SKILL.md call:
bashpython3From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
redhat.atlassian.netFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
PARENT_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Categorize Activity Types loads about 2.4k tokens when it runs. Until then it costs about 76 tokens; SKILL.md has 990 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from openshift-eng/ai-helpers at commit a627176, republished under its Apache-2.0 licence (© openshift-eng). 990 words, ~2,386 tokens.
.claude/skills/categorize-activity-types/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.Categorize Jira issues into Red Hat's Sankey capacity allocation categories and update them via MCP Jira tools. This skill supports two modes of operation:
/jira:categorize-activity-type)/jira:batch-categorize-activity-types)Both modes use identical classification logic, validation, and reporting.
These are the only valid values. Use the exact strings:
| Activity Type | Short Description |
|---|---|
| Associate Wellness & Development | Onboarding, training, AI learning, conferences, team health |
| Incidents & Support | Production incidents, customer escalations, on-call |
| Security & Compliance | CVEs, weaknesses, FedRAMP, compliance, security tooling |
| Quality / Stability / Reliability | Bugs, SLOs, chores, tech debt, toil reduction, PMR actions |
| Future Sustainability | Proactive architecture, productivity improvements, upstream, enablement |
| Product / Portfolio Work | New features, enhancements, strategic product/portfolio work |
For detailed definitions, subcategories, and edge cases, see resources/activity-type-guidance.md.
The Activity Type custom field ID is customfield_10464. This is the same across all projects on redhat.atlassian.net.
Before starting any work, verify MCP Jira tools are available:
searchJiraIssuesUsingJql with a simple query (e.g., jql: "project = OCM", maxResults: 1)Both modes write artifacts to .work/activity-type-classifier/. Create this directory before starting:
mkdir -p .work/activity-type-classifierCopy this checklist and track progress:
Classification Progress:
- [ ] Prerequisites: MCP Jira tools available
- [ ] Phase 1: Gather issues
- [ ] Phase 2: Categorize each issue
- [ ] Phase 3: Validate & generate report
- [ ] Phase 4: Apply updates (with approval)
- [ ] Phase 5: Iterate (batch mode only)Fetch the issue by key using getJiraIssue:
summary,description,issuetype,labels,parent,components,priority,customfield_10464customfield_10464 is not null), inform the user and stopParse user input for:
AND resolved >= "2025-01-01"Always filter for issues without an Activity Type set. The "Activity Type" is EMPTY condition is mandatory in every query — do not ask the user whether to include it.
Construct the JQL query using this template:
project = {PROJECT} AND issuetype = {TYPE} AND "Activity Type" is EMPTYCommon additions:
AND resolved >= "2025-01-01"AND status != ClosedExecute searchJiraIssuesUsingJql with maxResults: 50. If more results exist, make a second call with nextPageToken to get up to 100 total. Combine both result sets.
From each issue, extract: key, summary, description (truncate to 2000 chars), labels, issuetype, status, priority, comment, and parent. Save all extracted data to .work/activity-type-classifier/issues.json.
Report the count of issues found to the user before proceeding.
Pre-check — Parent inheritance: Before classifying each issue, check if it has a parent issue. If the parent has an Activity Type set (customfield_10464), inherit it directly — no further classification needed. Set confidence to "High" and reasoning to "Inherited from {PARENT_KEY}". To look up a parent's Activity Type, call getJiraIssue with the parent's key and check customfield_10464. Cache parent lookups to reduce API calls — multiple children may share the same parent.
For remaining issues (no parent or parent has no Activity Type), read summary, description, labels, comments, and status. Apply the classification rules below and the detailed guidance in resources/activity-type-guidance.md.
Save classifications to .work/activity-type-classifier/classifications.json as a JSON array:
[
{
"key": "OCM-12345",
"summary": "Issue title",
"activityType": "Product / Portfolio Work",
"confidence": "High",
"reasoning": "New customer-facing feature for cluster provisioning"
}
]In single-issue mode, this array contains exactly one entry. In batch mode, it contains all classified issues.
If total issues exceed 50 (batch mode), process in sub-batches of 20 to manage context.
Run the validation and report generation scripts. These are located in scripts/ relative to this skill's directory.
bash plugins/jira/skills/categorize-activity-types/scripts/validate-classifications.sh .work/activity-type-classifier/classifications.jsonpython3 plugins/jira/skills/categorize-activity-types/scripts/generate-report.py .work/activity-type-classifier/classifications.json .work/activity-type-classifier/report.md--auto-apply--auto-apply flag is present AND confidence is High: automatically update the Activity Type field without prompting--dry-run flag is present, skip this phase entirelyUse editJiraIssue to set customfield_10464 (Activity Type) to the classified value, e.g. {"value": "Product / Portfolio Work"}.
Updated OCM-12345: Activity Type set to "Product / Portfolio Work"
View at: https://redhat.atlassian.net/browse/OCM-12345After applying updates, offer to re-run the workflow:
When classifying an issue:
For the complete category definitions with subcategories and examples, see resources/activity-type-guidance.md.
| File | Purpose | When to Read |
|---|---|---|
| resources/activity-type-guidance.md | Full Sankey category definitions and subcategories | Phase 2 (classifying) |
| resources/report-template.md | Report format reference | Phase 3 (report generation) |
| scripts/validate-classifications.sh | Validate classifications JSON | Phase 3 (validation) |
| scripts/generate-report.py | Generate markdown report from JSON | Phase 3 (report generation) |
| scripts/cleanup.sh | Remove data artifacts, preserve reports | Post-workflow cleanup |
© openshift-eng, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 5 other files (scripts) in plugins/jira/skills/categorize-activity-types of openshift-eng/ai-helpers.
Open the folder on GitHubat commit a627176
Categorize Activity Types next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Categorize Activity Types this skillopenshift-eng/ai-helpers | 120 | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Link Ticket To SessionJayantDevkar/claude-code-karma | 329 | — | ~1.8k | Automated safety check: Notes | Apache-2.0 | |
| Jira Natural Language Interfacejjmartres/opencode | 133 | 3 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Issue Triage Loopcobusgreyling/loop-engineering | 11k | — | ~522 | Automated safety check: Pass | MIT | |
| Create Epic RecapDataDog/datadog-agent | 3.8k | — | ~5k | Automated safety check: Notes | Apache-2.0 | |
| Pilot Updatequay/quay | 2.8k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 |
JayantDevkar/claude-code-karma
Link the current Claude Code session to a ticket (Linear, Jira, GitHub Issues, or GitHub Pull Requests) and cache its title/status in karma.
jjmartres/opencode
Lets an agent view, create, update and transition Jira issues in natural language, automatically choosing between the jira CLI and Atlassian MCP tools.
cobusgreyling/loop-engineering
Scans open GitHub issues and discussions, flags duplicates, scores priority and proposes labels into issue-triage-state.md without ever labeling or closing.
DataDog/datadog-agent
A skill your agent uses when an engineer or manager asks to recap, summarize, or post an update on a Jira Epic — a progress update for an in-progress Epic (how far along it is, what's shipped so…
quay/quay
Post a biweekly Agentic SDLC pilot update comment to PROJQUAY-11352.
dnotitia/akb
Ingest whatever you point at into an AKB vault — a local file, a web URL, a GitHub PR/release/commit, a Confluence page, or a Jira issue.
openshift-eng/ai-helpers
Find and independently validate actionable reliability defects across OpenShift release jobs and presubmits, then export portable issue handoffs.
openshift-eng/ai-helpers
Fetch and address all PR review comments — categorize by priority, make code changes, post replies, and push.
openshift-eng/ai-helpers
Decide whether a GitHub PR has unanswered authorized review comments or new required CI failures worth a follow-up agent.
openshift-eng/ai-helpers
Analyze OpenShift must-gather diagnostic data including cluster operators, pods, nodes, and network components.
openshift-eng/ai-helpers
Schema for the autodl JSON data file produced by payload-analysis for database ingestion — you must use this skill whenever generating the autodl JSON file
openshift-eng/ai-helpers
State management for agentic payload triage actions — you must use this skill whenever reading or writing the payload results YAML file
Works with
Categorize Jira issues into Red Hat Sankey Activity Type categories using MCP Jira tools. Categorize Activity Types is an agent skill from openshift-eng/ai-helpers. Categorize Jira issues into Red Hat Sankey Activity Type categories using MCP Jira tools.
Categorize Activity Types fits situations like: the user wants to categorize; set activity types on Jira issues; mentions activity types; capacity allocation.
Run `npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a claude-code`. Or copy the skill folder (plugins/jira/skills/categorize-activity-types in openshift-eng/ai-helpers) into .claude/skills/categorize-activity-types in your project. Claude Code loads it when a task matches its description.
Run `npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a codex`. Or copy the skill folder (plugins/jira/skills/categorize-activity-types in openshift-eng/ai-helpers) into .agents/skills/categorize-activity-types in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add openshift-eng/ai-helpers --skill categorize-activity-types -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/categorize-activity-types, .gemini/skills/categorize-activity-types, .github/skills/categorize-activity-types and .opencode/skills/categorize-activity-types in your project.
Going by SKILL.md and its folder, Categorize Activity Types needs a shell and Python for the scripts in its folder, the command-line tools its instructions call (bash and python3) and credentials named PARENT_KEY. Our summary lists: Python 3; A Bash shell; A credential in PARENT_KEY.
SKILL.md names 1 domain. In commands or code: redhat.atlassian.net; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Categorize Activity Types is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.4k tokens (SKILL.md is roughly 9.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Categorize Activity Types: Link Ticket To Session (JayantDevkar/claude-code-karma, 329 stars), Jira Natural Language Interface (jjmartres/opencode, 133 stars), Issue Triage Loop (cobusgreyling/loop-engineering, 11k stars) and Create Epic Recap (DataDog/datadog-agent, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
openshift-eng (a GitHub organization) maintains it in openshift-eng/ai-helpers, which has 120 GitHub stars. The repository holds 118 skills in this directory. The repository was last updated on October 6, 2026.
Source: openshift-eng/ai-helpers on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.