Add Gitea issue pipelines and prompts using tea CLI
gt-issue-impl, gt-issue-research, gt-issue-rewrite, gt-issue-update pipelines with corresponding prompts. Mirrors the gh-issue-* variants but uses tea CLI with --login librete for Gitea authentication. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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.wave/pipelines/gt-issue-update.yaml
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182
.wave/pipelines/gt-issue-update.yaml
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kind: WavePipeline
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metadata:
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name: gt-issue-update
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description: "Refresh a stale Gitea issue by comparing it against recent codebase changes"
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release: true
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input:
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source: cli
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example: "public/librenotes 45 -- acceptance criteria are outdated after the worktree refactor"
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schema:
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type: string
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description: "owner/repo number [-- optional criticism or direction]"
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steps:
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- id: gather-context
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persona: gitea-analyst
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workspace:
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type: worktree
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branch: "{{ pipeline_id }}"
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exec:
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type: prompt
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source: |
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MANDATORY: You MUST call the Bash tool. NEVER say "tea CLI not installed" without trying.
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Input: {{ input }}
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Parse the input:
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- Split on " -- " to separate the repo+number from optional criticism.
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- The first part is "<owner/repo> <number>". Extract REPO (first token) and NUMBER (second token).
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- If there is text after " -- ", that is the user's CRITICISM about what's wrong with the issue.
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- If there is no " -- ", criticism is empty.
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Execute these commands using the Bash tool:
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1. tea --version
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2. Fetch the full issue:
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tea issues list --repo REPO --login librete -o json -f index,title,body,labels,state,url --limit 50
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Then filter the JSON for the issue matching NUMBER.
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3. Get commits since the issue was created (cap at 100):
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git log --since="<created_at>" --oneline -100
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4. Scan the issue body for file path references (anything matching patterns like
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`internal/...`, `cmd/...`, `.wave/...`, or backtick-quoted paths).
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For each referenced file, check if it still exists using `ls -la <path>`.
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5. Read CLAUDE.md for current project context:
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Read the file CLAUDE.md from the repository root.
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After gathering ALL data, produce a JSON result matching the contract schema.
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output_artifacts:
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- name: issue_context
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path: .wave/artifact.json
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type: json
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required: true
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handover:
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max_retries: 1
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contract:
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type: json_schema
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schema_path: .wave/contracts/issue-update-context.schema.json
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validate: true
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must_pass: true
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allow_recovery: true
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recovery_level: progressive
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progressive_validation: false
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- id: draft-update
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persona: gitea-analyst
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dependencies: [gather-context]
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memory:
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inject_artifacts:
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- step: gather-context
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artifact: issue_context
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as: context
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workspace:
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type: worktree
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branch: "{{ pipeline_id }}"
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exec:
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type: prompt
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source: |
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MANDATORY: You MUST call the Bash tool for any commands. NEVER generate fake output.
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The context artifact contains the gathered issue context.
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Your task: Compare the original issue against the codebase changes and draft an updated version.
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Step 1: Analyze each section of the issue body. Classify each as:
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- STILL_VALID: Content is accurate and up-to-date
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- OUTDATED: Content references old behavior, removed files, or superseded patterns
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- INCOMPLETE: Content is partially correct but missing recent developments
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- WRONG: Content is factually incorrect given current codebase state
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Step 2: If there is user criticism (non-empty "criticism" field), address EVERY point raised.
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The criticism takes priority — it represents what the issue author thinks is wrong.
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Step 3: Draft the updated issue:
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- Preserve sections classified as STILL_VALID (do not rewrite what works)
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- Rewrite OUTDATED and WRONG sections to reflect current reality
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- Expand INCOMPLETE sections with missing information
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- If the title needs updating, draft a new title
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- Append a "---\n**Changes since original**" section at the bottom listing what changed and why
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Step 4: If file paths in the issue body are now missing (from referenced_files.missing),
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update or remove those references.
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Produce a JSON result matching the contract schema.
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output_artifacts:
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- name: update_draft
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path: .wave/artifact.json
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type: json
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required: true
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handover:
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max_retries: 1
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contract:
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type: json_schema
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schema_path: .wave/contracts/issue-update-draft.schema.json
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validate: true
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must_pass: true
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allow_recovery: true
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recovery_level: progressive
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progressive_validation: false
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- id: apply-update
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persona: gitea-enhancer
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dependencies: [draft-update]
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memory:
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inject_artifacts:
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- step: draft-update
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artifact: update_draft
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as: draft
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- step: gather-context
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artifact: issue_context
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as: context
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workspace:
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type: worktree
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branch: "{{ pipeline_id }}"
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exec:
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type: prompt
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source: |
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CRITICAL: You MUST use the Bash tool for all commands. Do NOT generate fake output.
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Step 1: Use Bash tool to verify tea works:
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tea --version
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Step 2: Extract the repo and issue number from the available artifacts.
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Step 3: Apply the update:
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- If title_changed is true:
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tea issues edit <NUMBER> --repo <REPO> --login librete -t "<updated_title>"
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- Write the updated_body to a temp file, then apply it:
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Write updated_body to /tmp/issue-body.md
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tea issues edit <NUMBER> --repo <REPO> --login librete -d "$(cat /tmp/issue-body.md)"
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- Clean up /tmp/issue-body.md after applying.
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Step 4: Verify the update was applied:
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tea issues list --repo <REPO> --login librete -o json -f index,title,body,url --limit 50
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Then filter for the specific issue number.
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Compare the returned title and body against what was intended. Flag any discrepancies.
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Step 5: Record the results as a JSON object matching the contract schema.
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output_artifacts:
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- name: update_result
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path: .wave/artifact.json
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type: json
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required: true
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outcomes:
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- type: issue
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extract_from: .wave/artifact.json
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json_path: .url
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label: "Updated Issue"
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handover:
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max_retries: 1
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contract:
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type: json_schema
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schema_path: .wave/contracts/issue-update-result.schema.json
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validate: true
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must_pass: true
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allow_recovery: true
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recovery_level: progressive
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progressive_validation: false
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