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Kiro Verify Completion

CommunityPopular
gotalab
kiro-verify-completion

Verify completion and success claims with fresh evidence. Use before claiming a task is complete, a fix works, tests pass, or a feature is ready for GO.

Overview

Publishergotalab
Repositorycc-sdd
Skill namekiro-verify-completion
Stars
3.7K
Forks
283
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Kiro Verify Completion 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-verify-completion .claude/skills/kiro-verify-completion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kiro Verify Completion 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 Verify Completion 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 Verify Completion 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.

kiro-verify-completion

<background_information> This skill prevents false completion claims. A task, fix, or feature is only complete when supported by fresh evidence that matches the scope of the claim. </background_information>

  • Before saying a task is complete
  • Before saying a bug is fixed
  • Before saying tests pass
  • Before moving to the next task in autonomous execution
  • Before reporting GO from feature-level validation
  • Before trusting another subagent's success report

Do not use this skill for early planning or speculative status updates.

Inputs

Provide:

  • The exact claim to verify
  • Claim type:
    • TASK
    • FIX
    • TEST_OR_BUILD
    • FEATURE_GO
  • Validation commands discovered by the controller
  • Fresh command output and exit codes
  • Relevant task IDs, requirement IDs, and design refs where applicable
  • For feature-level claims:
    • requirements coverage status
    • design alignment status
    • integration status
    • blocked task status

Outputs

Return one of:

  • VERIFIED
  • NOT_VERIFIED
  • MANUAL_VERIFY_REQUIRED

Also return:

  • Claim reviewed
  • Evidence used
  • Scope/evidence mismatch, if any

Use the language specified in spec.json.

Gate Function

  1. Identify the exact claim.
  2. Identify the exact command or checklist that proves that claim.
  3. Require fresh evidence from the current code state.
  4. Check exit code, failure count, skipped scope, and missing coverage.
  5. Reject claims that are broader than the evidence.
  6. If mandatory validation cannot be completed, return MANUAL_VERIFY_REQUIRED.
  7. Only then allow the claim.

Claim-Specific Rules

TASK

Require:

  • task-local verification evidence
  • no unresolved blocking findings from review
  • evidence aligned with the task boundary

FIX

Require:

  • evidence that the original symptom is resolved
  • no broader regressions in the relevant verification scope

TEST_OR_BUILD

Require:

  • actual command output
  • exit code
  • no inference from unrelated checks

FEATURE_GO

Require:

  • full test suite result
  • runtime smoke boot result showing the built artifact reaches its first usable state
  • requirements coverage assessment
  • cross-task integration assessment
  • design end-to-end alignment assessment
  • blocked tasks assessment

A passing test suite alone is not enough for FEATURE_GO.

Stop / Escalate

Return MANUAL_VERIFY_REQUIRED when:

  • No canonical validation command is known
  • The required environment is unavailable
  • A mandatory manual verification step cannot be executed

Return NOT_VERIFIED when:

  • The command failed
  • Evidence is stale
  • Evidence is partial
  • The claim exceeds the evidence
  • The feature still has unresolved blocked tasks or uncovered requirements

Common Rationalizations

RationalizationReality
“The subagent said it succeeded”Reported success is not verification evidence.
“Tests passed earlier”Fresh evidence only.
“Build should be fine because lint passed”Lint does not prove build success.
“Tests passed and build succeeded, so it must run”Type erasure, module loading, native ABI, and boot-time config issues can still fail at runtime.
“The feature is done because all tasks are checked off”FEATURE_GO also requires coverage, integration, and design alignment.

Output Format

md
## Verification Result
- STATUS: VERIFIED | NOT_VERIFIED | MANUAL_VERIFY_REQUIRED
- CLAIM_TYPE: TASK | FIX | TEST_OR_BUILD | FEATURE_GO
- CLAIM: <exact claim>
- EVIDENCE: <command/checklist and result>
- GAPS: <scope/evidence mismatch or missing validation>
- NOTES: <next action if not verified>

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Kiro Verify Completion AI skill do?

Verify completion and success claims with fresh evidence. Use before claiming a task is complete, a fix works, tests pass, or a feature is ready for GO.

Why use Kiro Verify Completion on TypingMind?

Because you install it once and use it with any model. Kiro Verify Completion 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 Verify Completion 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-verify-completion. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Kiro Verify Completion?

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 Verify Completion?

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

Is the Kiro Verify Completion 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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