Ring:Implementing Tasks logo

Ring:Implementing Tasks

Organization
LerianStudio
ring:implementing-tasks

Implementing a single planned task (Task N.M.T) end-to-end: selects the right backend agent by language and service type, drives one TDD RED->GREEN turn, then verifies coverage, lint, license headers, runtime, and delivery before handoff. Runs as Gate 0 before ring:reviewing-code. Use to drive ONE task inside an already-running cycle. Skip when asked to implement a whole plan.md or multiple tasks (use ring:running-dev-cycle).

Overview

PublisherLerianStudio
Repositoryring
Skill namering:implementing-tasks
Stars
215
Forks
28
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by LerianStudio on GitHub. Read the source before you install it.

Installation

Install the Ring:Implementing Tasks AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LerianStudio/ring.git /tmp/ring
mkdir -p .claude/skills
cp -r /tmp/ring/dev-team/skills/implementing-tasks .claude/skills/lerianstudio-ring-implementing-tasks
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ring:Implementing Tasks in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ring:Implementing Tasks on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ring:Implementing Tasks is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Implementation (Gate 0)

When to use

  • Gate 0 of development cycle
  • Tasks loaded at initialization
  • Ready to write code

Skip when

  • Not inside a development cycle (ring:running-dev-cycle or ring:planning-backend-refactor)
  • Task is documentation-only, configuration-only, or non-code
  • Implementation already completed for the current gate

Sequence

Runs before: ring:reviewing-code

Related

Complementary: ring:running-dev-cycle, ring:test-driven-development, ring:reviewing-code

You orchestrate. Agents implement. Select the agent, prepare the prompt, track state, validate outputs.

Step 1: Validate Input

The unit of work is a single task (Task N.M.T, e.g. Task 1.1.1) from the phased plan. Its requirements arrive inline from the orchestrator, which reads the task block under its epic in plan.md: Context, Implementation vision, Files, Verification, and Done when.

Required: unit_id (the task's Task N.M.T id), requirements (the task block), language (go|typescript|python), service_type (api|worker|batch|cli|frontend|bff). Optional: technical_design, existing_patterns, project_rules_path (default: docs/PROJECT_RULES.md).

STOP if any required input is missing.

Step 2: Validate Prerequisites

Check PROJECT_RULES.md exists at project_rules_path → STOP if not found.

Agent selection:

LanguageService TypeAgent
goapi, worker, batch, cliring:backend-go
typescriptapi, workerring:backend-ts
typescriptfrontend, bffring:bff-ts

Step 3: Gate 0 — TDD (RED → GREEN)

Dispatch the selected agent ONCE. The agent writes the failing test, captures the RED failure output as evidence, then implements to GREEN — in one turn.

yaml
Task:
  subagent_type: "{selected_agent}"
  description: "Gate 0 TDD (RED→GREEN) for {unit_id}"
  prompt: |
    ## TDD: write a failing test, then make it pass

    unit_id: {unit_id}
    requirements: {requirements}
    language: {language}
    service_type: {service_type}

    Standards: load via state.cached_standards or WebFetch Ring standards for the language.
    Project rules: {project_rules_path}

    ## Frontend TDD policy (React/Next.js only)
    Visual-only components (layout, styling, animations): RED not required — report
    "Visual-only → RED skipped; visual checks apply in the frontend flow."
    Behavioral components (hooks, validation, state, conditional rendering, API): RED required.

    ## Multi-Tenant (Go only)
    Implement DUAL-MODE from the start. Use resolvers for all resources
    (tmcore.GetPGContext, tmcore.GetMBContext, etc.) — they work transparently
    in single-tenant and multi-tenant mode. Load multi-tenant.md for patterns.

    ## Your task
    1. Write a test capturing expected behavior; run it; it MUST fail (no implementation yet); capture the failure output.
    2. Implement the minimum code to make the test pass; run tests — all pass.
    3. Enforce coverage threshold (Ring minimum 85%, PROJECT_RULES may raise it).
    4. Create/update docker-compose and .env.example when the service needs local dependencies.
    5. Verify local runtime starts cleanly for the changed service path; verify basic health/observability for the changed code.
    6. Write delivery verification results.
    7. Commit: "{feat|fix|test|chore}(scope): description".

    ## Required output
    - RED: test file path + the actual failure output (MANDATORY — must contain FAIL)
    - GREEN: implementation files + test pass output
    - Coverage report (must meet threshold)
    - Local runtime: docker-compose/.env.example status or explicit "not required"
    - Basic health/observability verification
    - Delivery verification: requirements delivered, dead-code check, files changed
    - Git commit SHA

Validate output: the RED failure output must contain "FAIL" (evidence the test failed before implementation existed), and the GREEN output must show PASS with coverage ≥ threshold. Re-dispatch if RED evidence is missing or tests do not pass.

Step 4: Gate 0 Exit — Delivery Verification

After TDD-GREEN passes, verify delivery:

Automated checks (run on all files changed by Gate 0):

bash
# A. File size (>1500 = FAIL, >1000 = PARTIAL unless cohesion justified)
find . -name "*.go" ! -name "*_test.go" ! -path "*/generated/*" \
  -exec wc -l {} + | awk '$1 > 1000'

# B. License headers
for f in $files_changed; do
  head -10 "$f" | grep -qiE 'copyright|licensed|spdx|license' || echo "MISSING: $f"
done

# C. Lint (go: golangci-lint; ts: eslint)
golangci-lint run ./... || echo "LINT FAILED"

# D. Coverage (Ring minimum 85%; PROJECT_RULES.md can raise)
# Go example: go test ./... -cover
# TypeScript example: npm test -- --coverage

# E. Local runtime / docker-compose
# If docker-compose.yml is required, verify it can config and start the changed service dependencies.

# F. Migration safety (if SQL migrations changed)
# Check for blocking ops: ADD COLUMN NOT NULL without DEFAULT, DROP COLUMN,
# CREATE INDEX without CONCURRENTLY, ALTER COLUMN TYPE, TRUNCATE

Verdict:

  • PASS: all requirements delivered, 0 dead code, all checks pass
  • PARTIAL: some requirements delivered → list gaps, return to Gate 0
  • FAIL: critical requirements missing → return to Gate 0 with explicit instructions

Step 5: Commit

When Step 4 verdict is PASS, load and call ring:committing-changes to create the signed atomic commit for this task before returning control to the dev-cycle orchestrator.

yaml
Skill("ring:committing-changes")

MUST only run on PASS. On PARTIAL or FAIL, return to Gate 0 — do NOT commit.

Output Format

markdown
## Implementation Summary
- unit_id, agent used, TDD phase results

## TDD Results
- RED: test file path + failure output
- GREEN: test pass output + coverage

## Files Changed
- List of created/modified files

## Delivery Verification
- Each requirement: DELIVERED or NOT DELIVERED
- Automated checks: PASS/FAIL per check

## Handoff to Next Gate
- files_changed list for Gate 8 review
- ready_for_review: YES or NO
- Verdict: PASS | PARTIAL | FAIL

Frequently asked questions

What does the Ring:Implementing Tasks AI skill do?

Implementing a single planned task (Task N.M.T) end-to-end: selects the right backend agent by language and service type, drives one TDD RED->GREEN turn, then verifies coverage, lint, license headers, runtime, and delivery before handoff. Runs as Gate 0 before ring:reviewing-code. Use to drive ONE task inside an already-running cycle. Skip when asked to implement a whole plan.md or multiple tasks (use ring:running-dev-cycle).

Why use Ring:Implementing Tasks on TypingMind?

Because you install it once and use it with any model. Ring:Implementing Tasks is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ring:Implementing Tasks in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LerianStudio/ring/tree/main/dev-team/skills/implementing-tasks. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ring:Implementing Tasks?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ring:Implementing Tasks?

As many as you like. As long as a model supports skills, you can use Ring:Implementing Tasks with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ring:Implementing Tasks AI skill free?

Yes. It is published on GitHub by LerianStudio under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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