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Kiro Spec Status

CommunityPopular
gotalab
kiro-spec-status

Show specification status and progress

Overview

Publishergotalab
Repositorycc-sdd
Skill namekiro-spec-status
Stars
3.7K
Forks
283
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepository
  • 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 gotalab on GitHub. Read the source before you install it.

Installation

Install the Kiro Spec Status 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/gotalab/cc-sdd.git /tmp/cc-sdd
mkdir -p .claude/skills
cp -r /tmp/cc-sdd/tools/cc-sdd/templates/agents/antigravity-skills/skills/kiro-spec-status .claude/skills/kiro-spec-status
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kiro Spec Status 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 Kiro Spec Status 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 Kiro Spec Status 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.

Specification Status

<background_information>

  • Success Criteria:
    • Show current phase and completion status
    • Identify next actions and blockers
    • Provide clear visibility into progress
    • Surface boundary readiness, upstream/downstream context, and likely revalidation needs when available </background_information>

Step 1: Load Spec Context

  • Read {{KIRO_DIR}}/specs/$1/spec.json for metadata and phase status
  • Read {{KIRO_DIR}}/specs/$1/brief.md if it exists
  • Read existing files: requirements.md, design.md, tasks.md (if they exist)
  • Check {{KIRO_DIR}}/specs/$1/ directory for available files
  • Read {{KIRO_DIR}}/steering/roadmap.md if it exists and this spec appears in it

Step 2: Analyze Status

Parse each phase:

  • Requirements: Count requirements and acceptance criteria
  • Design: Check for architecture, components, diagrams, and whether boundary sections are present
  • Tasks: Count completed vs total tasks (parse - [x] vs - [ ])
  • Approvals: Check approval status in spec.json
  • Boundary context:
    • From brief.md: note Boundary Candidates, Upstream / Downstream, and Existing Spec Touchpoints if present
    • From design.md: note Boundary Commitments, Out of Boundary, Allowed Dependencies, and Revalidation Triggers if present
    • From roadmap.md: note upstream dependencies and whether this spec is adjacent to Existing Spec Updates
  • Revalidation watchlist:
    • Identify downstream specs, neighboring existing-spec updates, or rollout-sensitive design notes that may need revalidation if this spec changes
    • Call out when the current spec shape looks too broad and may want roadmap/design splitting instead of more local repair

Step 3: Generate Report

Create report in the language specified in spec.json covering:

  1. Current Phase & Progress: Where the spec is in the workflow
  2. Completion Status: Percentage complete for each phase
  3. Task Breakdown: If tasks exist, show completed/remaining counts
  4. Boundary Context: Upstream/downstream, out-of-boundary, and allowed dependency notes when available
  5. Revalidation Watchlist: Downstream or adjacent work likely affected by changes to this spec
  6. Next Actions: What needs to be done next
  7. Blockers: Any issues preventing progress

Safety & Fallback

Error Scenarios

Spec Not Found:

  • Message: "No spec found for $1. Check available specs in {{KIRO_DIR}}/specs/"
  • Action: List available spec directories

Incomplete Spec:

  • Warning: Identify which files are missing
  • Suggested Action: Point to next phase command

List All Specs

To see all available specs:

  • Run with no argument or use wildcard
  • Shows all specs in {{KIRO_DIR}}/specs/ with their status

Frequently asked questions

What does the Kiro Spec Status AI skill do?

Show specification status and progress

Why use Kiro Spec Status on TypingMind?

Because you install it once and use it with any model. Kiro Spec Status 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 Kiro Spec Status in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gotalab/cc-sdd/tree/main/tools/cc-sdd/templates/agents/antigravity-skills/skills/kiro-spec-status. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Kiro Spec Status?

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 Kiro Spec Status?

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

Is the Kiro Spec Status AI skill free?

Yes. It is published on GitHub by gotalab under the MIT 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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