Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/CodySwannGT/lisa --skill lisa-jira-journeyコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか?SkillsMP が現在取得できるファイルをダウンロードできます。
SKILL.md を表示中
| name | lisa-jira-journey |
| description | Parse a JIRA ticket's… |
| allowed-tools | ["Bash","Read","Glob","Grep","Skill"] |
All Atlassian operations in this skill go through lisa-atlassian-access. Do not call MCP tools or acli directly. Note: the helper scripts (scripts/parse-plan.py, scripts/jira-evidence/post-evidence.sh) currently use direct API calls and are pending migration to route through atlassian-access.
Parse a JIRA ticket's Validation Journey, execute the verification steps using the appropriate tools for the change type, capture evidence at each typed [EVIDENCE: <artifact-type>: <name>] marker, and post to JIRA + GitHub PR.
$ARGUMENTS: <TICKET_ID> [PR_NUMBER]
TICKET_ID (required): JIRA ticket key (e.g., PROJ-123)PR_NUMBER (optional): GitHub PR number to update descriptionJIRA_API_TOKEN environment variable setjira-cli configured — .lisa/jira-cli/.config.yml (written by the
setup-jira-cli SessionStart hook) or ~/.config/.jira/.config.ymlgh CLI authenticatedRun the parser script to extract the Validation Journey from the JIRA ticket description:
python3 .claude/skills/jira-journey/scripts/parse-plan.py <TICKET_ID>
The parser resolves Jira configuration from the checkout first: it searches
$CLAUDE_PROJECT_DIR/.lisa/jira-cli/.config.yml, then the current directory and
its parents, and only then falls back to ~/.config/.jira/.config.yml. Do not
copy project settings into the home-level file just to make this step work.
The script outputs JSON with: ticket, prerequisites, steps, viewports, assertions.
Note: viewports may be empty for TypeScript tickets — that is expected.
Before starting the journey, verify each prerequisite:
Execute each step sequentially. For each step, determine the verification approach based on the step text and change type:
evidence/NN-name.txtevidence/NN-name.txtevidence/NN-name.txtevidence/NN-name.txtevidence/NN-name.txtAt each typed [EVIDENCE: <artifact-type>: <name>] marker, capture an artifact of the declared type — the type is the contract, not a suggestion:
screenshot / recording → an actual image/video file from the driven UI (Playwright, simulator), never a text description of what was seenhttp-transcript → the exact request (curl command or client call) plus the full responsecli-output → the command plus stdout/stderr and exit codelog-snippet → the correlated log lines pulled from the running systemdb-query-output → the query plus returned rowsperf-trace → the benchmark/frame-timing/profiler output with methodology (device profile, dataset size)test-run-log → reporter output naming the spec and showing it ran and passeddeploy-log / state-dump → the deployment/health-check output or observed-state JSONA prose claim ("the error state rendered gracefully") satisfies no marker. Legacy untyped markers: infer the type from the step's action, capture accordingly, and note the inference. Write each artifact to a numbered file:
Treat only exact [EVIDENCE: ...] markers (plus the legacy local [SCREENSHOT: ...] form) as capture instructions. Both the canonical [EVIDENCE-REF: <work-item-ref> | <artifact-type>: <kebab-case-name>] and the Lisa 2.223.0 legacy alias [EVIDENCE-REF: <tracker-ref>: <artifact-type>: <kebab-case-name>] point to another work item's artifact: preserve either as explanatory text, but do not capture it, assign it a sequence number, include it in duplicate-name checks, or count it as a local manifest entry. If a runtime-changing leaf has references but no local claiming marker, stop because S14 is unsatisfied.
Evidence files are named: {NN}-{evidence-name}.{ext} — extension matches the declared artifact type (.png/.webm for screenshot/recording, .txt for transcripts/logs/output, .json for structured state)
NN: zero-padded sequential number (01, 02, 03...)evidence-name: the <name> part of the typed marker in the JIRA stepExample:
evidence/
01-health-check.json
02-schema-after-migration.txt
03-rate-limit-response.txt
comment.txt
comment.md
After capturing all evidence, run the template generator:
python3 .claude/skills/jira-journey/scripts/generate-templates.py \
<TICKET_ID> \
<PR_NUMBER> \
<BRANCH_NAME> \
./evidence
This generates evidence/comment.txt (JIRA wiki markup) and evidence/comment.md (GitHub markdown) with evidence formatted as code blocks.
Use the jira-evidence skill to post everything:
bash .claude/skills/jira-evidence/scripts/post-evidence.sh <TICKET_ID> ./evidence <PR_NUMBER>
Confirm evidence is posted to both the JIRA ticket and GitHub PR.
The agent should use patterns from the project's verfication.md when executing steps:
| Change Type | Verification Method | Evidence Format |
|---|---|---|
| API endpoint | curl -s localhost:PORT/endpoint | JSON response |
| Database migration | psql -c "\d table" or migration output | Schema text |
| Background job | Trigger + check state | Log output |
| Library/utility | bun run test -- path/to/test | Test output |
| Security fix | Reproduce + verify fix | Request/response |
| Auth/authz | Multi-role verification | Status codes per role |
Ensure the command succeeded and produced output. Use 2>&1 to capture both stdout and stderr.
The ticket may not have a Validation Journey section. Use /jira-add-journey <TICKET_ID> to add one.