gitea-workflow

jwynia/agent-skills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/jwynia/agent-skills --skill gitea-workflow
0 commentsdiscussion
summary

A skill that guides agents through structured agile development workflows for Gitea repositories by intelligently invoking commands in sequence. Uses checkpoint-based flow control to auto-progress between steps while pausing at key decision points.

skill.md

Gitea Workflow Orchestrator

A skill that guides agents through structured agile development workflows for Gitea repositories by intelligently invoking commands in sequence. Uses checkpoint-based flow control to auto-progress between steps while pausing at key decision points.

When to Use This Skill

Use this skill when:

  • Working with a Gitea-hosted repository
  • Starting work for the day ("run morning standup", "start my day")
  • Working on a task ("implement next task", "continue working")
  • Completing a development cycle ("finish this task", "prepare PR")
  • Running sprint ceremonies ("start sprint", "end sprint", "retrospective")
  • Resuming interrupted work ("what's next", "where was I")

Do NOT use this skill when:

  • Working with GitHub repositories (use agile-workflow instead)
  • Running a single specific command (use that command directly)
  • Just checking status (use /status directly)
  • Only doing code review without full cycle (use /review-code directly)
  • Researching or planning without implementation

Prerequisites

Before using this skill:

  • Git repository initialized with worktree support
  • Gitea Tea CLI installed and authenticated (tea login)
  • Context network with backlog structure at context-network/backlog/
  • Task status files at context-network/backlog/by-status/*.md
  • GITEA_URL environment variable set (or configured in tea)
  • GITEA_TOKEN environment variable set for API scripts

Workflow Types Overview

WORKFLOW TYPES
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

TASK CYCLE (Primary)     DAILY                SPRINT
──────────────────────   ──────────────────   ──────────────────
sync                     Morning:             Start:
  ↓                        sync --last 1d       sync --all
next → [CHECKPOINT]        status --brief       groom --all
  ↓                        groom --ready        plan sprint-goals
implement                                       status
  ↓                      Evening:
[CHECKPOINT]               checklist          End:
  ↓                        discovery            sync --sprint
review-code                sync --last 1d       retrospective
review-tests                                    audit --sprint
  ↓                                             maintenance --deep
[CHECKPOINT]
apply-recommendations (if issues)
pr-prep → [CHECKPOINT]
pr-complete
update-backlog & status
END
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

State Detection

The skill determines current workflow state automatically. No manual tracking needed.

Detection Signals

Signal How to Check Indicates
Worktree exists git worktree list Task in progress
Task branch active git branch --show-current matches task/* Active implementation
Uncommitted changes git status --porcelain Active coding
PR exists tea pulls list --state open In review
PR merged tea pulls + check state Ready for cleanup

State Matrix

STATE DETECTION LOGIC
─────────────────────────────────────────────────────────────
Check                           → State           → Next Step
─────────────────────────────────────────────────────────────
No worktree, no in-progress     → IDLE            → sync, next
Worktree exists, uncommitted    → IMPLEMENTING    → continue implement
Worktree exists, all committed  → READY_REVIEW    → review-code
PR open, CI pending             → AWAITING_CI     → wait or address
PR open, CI pass                → READY_MERGE     → pr-complete
PR merged, worktree exists      → CLEANUP         → pr-complete
─────────────────────────────────────────────────────────────

For detailed detection algorithms, see references/state-detection.md.

Invocation Patterns

# Auto-detect state and continue from where you are
/gitea-workflow

# Start specific workflow phase
/gitea-workflow --phase task-cycle
/gitea-workflow --phase daily-morning
/gitea-workflow --phase daily-evening
/gitea-workflow --phase sprint-start
/gitea-workflow --phase sprint-end

# Resume work on specific task
/gitea-workflow --task TASK-123

# Preview what would happen without executing
/gitea-workflow --dry-run

Task Cycle Phase

The primary workflow for completing a single task from selection to merge.

Step 1: Sync Reality

Ensure context network matches actual project state.

Run: sync --last 1d --dry-run
Purpose: Detect drift between documented and actual state
Output: Sync report showing completions, partial work, divergences

Step 2: Select Task

Identify the next task to work on.

Run: next
Purpose: Find highest priority ready task
Output: Task ID, title, branch name suggestion

CHECKPOINT: TASK_SELECTED

  • Pause to confirm task selection
  • User can accept or choose different task
  • On accept: continue to implementation

Step 3: Implement

Test-driven development in isolated worktree.

Run: implement [TASK-ID]
Purpose: Create worktree, write tests first, implement, verify
Output: Working implementation with passing tests

CHECKPOINT: IMPL_COMPLETE

  • Pause after implementation completes
  • Show test results and coverage
  • On success: continue to review

Step 4: Review

Quality validation of implementation.

Run: review-code --uncommitted
Run: review-tests --uncommitted
Purpose: Identify quality issues, security concerns, test gaps
Output: Review reports with issues and recommendations

CHECKPOINT: REVIEWS_DONE

  • Display combined review results
  • If critical issues: must address before continuing
  • If no issues: auto-continue to PR prep
  • User decides: apply recommendations now or defer

Step 5: Apply Recommendations (Conditional)

Address review findings intelligently.

Run: apply-recommendations [review-output]
Purpose: Apply quick fixes now, defer complex changes to tasks
Output: Applied fixes + created follow-up tasks

Step 6: Prepare PR

Create pull request with full documentation.

Run: pr-prep
Purpose: Validate, document, and create PR
Output: PR created with description, tests verified

CHECKPOINT: PR_CREATED

  • Display PR URL and CI status
  • Wait for CI checks to complete (verify manually or via API script)
  • On CI pass + approval: continue to merge
  • On CI fail: stop, address issues

Step 7: Complete PR

Merge and cleanup.

Run: pr-complete [PR-NUMBER]
Purpose: Merge PR, delete branch, remove worktree, update status
Output: Task marked complete, cleanup done

Step 8: Update Backlog and Project Status

Persist progress to source-of-truth documentation.

Run: Part of pr-complete (Phase 6)
Purpose: Update epic file (task → complete), unblock dependents, update project status
Output: Backlog and project status reflect actual progress

Why this step matters: Without it, completed tasks remain marked "ready" in backlog files and project status stays stale. Internal tracking files are session-scoped; the backlog and status files are the persistent source of truth.

For detailed task-cycle instructions, see references/phases/task-cycle.md.

Daily Phase

Quick sequences for start and end of workday.

Morning Standup (~5 min)

Run sequence:
1. sync --last 1d --dry-run   # What actually happened yesterday
2. status --brief --sprint    # Current sprint health
3. groom --ready-only         # What's ready to work on

Output: Clear picture of today's priorities

Evening Wrap-up (~10 min)

Run sequence:
1. checklist                  # Ensure nothing lost
2. discovery                  # Capture learnings
3. sync --last 1d            # Update task statuses

Output: Knowledge preserved, state synchronized

For detailed daily instructions, see references/phases/daily.md.

Sprint Phase

Ceremonies for sprint boundaries.

Sprint Start (~60 min)

Run sequence:
1. sync --all                 # Full reality alignment
2. groom --all               # Comprehensive grooming
3. plan sprint-goals         # Architecture and goals
4. status --detailed         # Baseline metrics

Output: Sprint plan with groomed, ready backlog

Sprint End (~90 min)

Run sequence:
1. sync --sprint             # Final sprint sync
2. retrospective             # Capture learnings
3. audit --scope sprint      # Quality review
4. status --metrics          # Sprint metrics
5. maintenance --deep        # Context network cleanup

Output: Sprint closed, learnings captured, ready for next

For detailed sprint instructions, see references/phases/sprint.md.

Checkpoint Handling

Checkpoints are pauses for human decision-making.

Checkpoint Behavior

At each checkpoint:

  1. Summarize what just completed
  2. Show key results and any issues
  3. Present next steps
  4. Wait for user input

Checkpoint Responses

Response Action
"continue" / "proceed" / "yes" Move to next step
"stop" / "pause" Save state, exit workflow
"back" Re-run previous step
"skip" Skip current step (use cautiously)
Custom input May adjust next step parameters

Auto-Continue Conditions

Some checkpoints can auto-continue when conditions are met:

Checkpoint Auto-Continue If
IMPL_COMPLETE All tests pass, build succeeds
REVIEWS_DONE No critical or high severity issues
PR_CREATED CI passes (verified via API), required approvals obtained

For detailed checkpoint handling, see references/checkpoint-handling.md.

Command Reference

Each workflow step uses embedded command instructions:

Command Reference Purpose
sync references/commands/sync.md Reality synchronization
groom references/commands/groom.md Task refinement
next references/commands/next.md Task selection
implement references/commands/implement.md TDD implementation
review-code references/commands/review-code.md Code quality review
review-tests references/commands/review-tests.md Test quality review
apply-recommendations references/commands/apply-recommendations.md Triage and apply fixes
pr-prep references/commands/pr-prep.md PR creation
pr-complete references/commands/pr-complete.md PR merge and cleanup
discovery references/commands/discovery.md Learning capture
retrospective references/commands/retrospective.md Post-work analysis
maintenance references/commands/maintenance.md Context network cleanup

Example: Complete Task Cycle

Scenario: Start of day, implement next available task

Invocation:

/gitea-workflow --phase task-cycle

Flow:

Agent: Detecting current state...
       No worktree found, checking ready tasks...

Agent: Running sync --last 1d --dry-run
       [Sync output: 0 tasks completed but undocumented]

Agent: Running next
       Found: TASK-042 - Add user preferences endpoint
       Priority: High | Size: Small | Branch: task/TASK-042-preferences

       ╔═══════════════════════════════════════════╗
       ║  CHECKPOINT: Task Selection               ║
       ╠═══════════════════════════════════════════╣
       ║  Selected: TASK-042                       ║
       ║  Proceed with implementation?             ║
       ║                                           ║
       ║  [continue] [stop] [other task]           ║
       ╚═══════════════════════════════════════════╝

User: continue

Agent: Creating worktree at .worktrees/TASK-042/
       Running implement TASK-042
       [Implementation proceeds with TDD...]

       Tests: 12 passing
       Coverage: 87%
       Build: Success

       ╔═══════════════════════════════════════════╗
       ║  CHECKPOINT: Implementation Complete      ║
       ╠═══════════════════════════════════════════╣
       ║  All tests passing, ready for review      ║
       ║  Proceed to code review?                  ║
       ║                                           ║
       ║  [continue] [stop]                        ║
       ╚═══════════════════════════════════════════╝

[Flow continues through review, PR, merge...]

Gitea-Specific Notes

CI Status Checking

Gitea uses external CI systems (Drone, Woodpecker, Jenkins, etc.). To check CI status:

  1. Via API Script: Use scripts/gitea-ci-status.sh to query commit statuses
  2. Manual Verification: Check your CI dashboard directly
  3. PR Mergeability: Check if PR shows as mergeable in Gitea UI

Tea CLI Command Reference

Operation
how to use gitea-workflow

How to use gitea-workflow on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add gitea-workflow
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jwynia/agent-skills --skill gitea-workflow

The skills CLI fetches gitea-workflow from GitHub repository jwynia/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/gitea-workflow

Reload or restart Cursor to activate gitea-workflow. Access the skill through slash commands (e.g., /gitea-workflow) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.771 reviews
  • Amelia Liu· Dec 28, 2024

    Solid pick for teams standardizing on skills: gitea-workflow is focused, and the summary matches what you get after install.

  • Daniel Harris· Dec 24, 2024

    Registry listing for gitea-workflow matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Amelia Farah· Dec 16, 2024

    We added gitea-workflow from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kabir Abbas· Dec 16, 2024

    Keeps context tight: gitea-workflow is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Daniel White· Dec 12, 2024

    gitea-workflow is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Shikha Mishra· Dec 8, 2024

    Keeps context tight: gitea-workflow is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aditi Garcia· Dec 8, 2024

    Keeps context tight: gitea-workflow is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Rahul Santra· Nov 27, 2024

    gitea-workflow has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Aanya Bansal· Nov 27, 2024

    gitea-workflow has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Amelia Rahman· Nov 23, 2024

    gitea-workflow fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

showing 1-10 of 71

1 / 8