Mission Verify logo

Mission Verify

Organization
tikalk
mission-verify

Use when implemented work must be judged against its brief — severity-ranked findings plus one converge verdict of DONE, CONTINUE or SPEC_CORRECTION_NEEDED.

Overview

Publishertikalk
Repositoryadlc-team-skills
Skill namemission-verify
Stars
144
Forks
2
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Mission Verify 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.
    https://github.com/tikalk/adlc-team-skills/tree/main/skills/mission/mission-verify
  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/tikalk/adlc-team-skills.git /tmp/adlc-team-skills
mkdir -p .claude/skills
cp -r /tmp/adlc-team-skills/skills/mission/mission-verify .claude/skills/mission-verify
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mission Verify 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 Mission Verify 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 Mission Verify 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.

mission-verify

Requires: the factory-mission skill's shared executor contract at .agents/skills/factory-mission/references/executor.md (installed path); install with adlc-cli skills add tikalk/adlc-team-skills --skill factory-mission.

In a local session — you answer the gates

When ADLC_RUN_ID is not set, a person is in this session, and nothing else will answer a gate. The agentic-container runtime that relays gates to Slack exists only in a runner pod.

  1. A paused run is your turn, not the end of the mission. When adlc-cli workflow run or resume exits with the run paused at a gate (run_paused, status: paused in adlc-cli workflow state show <run_id>), ask the person the gate's question and options. Then run adlc-cli workflow resume <run_id> --input <verdict_input>=<answer> and keep going. Never end your turn on a paused run that nobody was asked about.
  2. Every gate that approves MRs is followed by a step that opens them. A gate whose message promises MRs/PRs is followed by a publish step: run-branch.sh and open-mr.sh for each repository the change touches, writing mr_url (mr_urls for more than one). Only then comes the write-back step, so the completion comment links real MRs. A gate with nothing after it to act on its answer is a plan defect; fix the plan before you start the run.
  3. Before ending your turn, the run is completed, failed or aborted, or it is paused at a gate the person has been asked about.

What this skill does

mission-verify owns the verify phase of the mission SDD family: it judges the built work against the brief rather than the implementer's claims, emits severity-ranked findings, and returns one converge verdict. It works under the shared executor contract (.agents/skills/factory-mission/references/executor.md): the verify step reads the test and code artifacts and emits findings, and the converge step reads brief.md and emits a decision — the judge is independent, so it checks the brief and non-goals rather than the verifier's own findings. It stops at the verdict — REVIEW and SHIP belong to factory-review and factory-deploy, which this skill never pre-empts.

Default lane

  1. Read the artifact refs produced by the test and code steps.
  2. Judge against brief.md, not the implementer's claims — re-run the suite, inspect the diff, and confirm the non-goals are untouched. The converge judge works from the brief and non-goals, never from the verifier's own findings.
  3. Emit severity-ranked findings as Critical, Important or Minor, each tied to evidence in the diff, the suite output or an untouched non-goal.
  4. Return one converge verdict: DONE when the criteria are met and the quality threshold is reached, CONTINUE when in-scope gaps remain, SPEC_CORRECTION_NEEDED when a criterion is unmeasurable or the scope conflicts.
  5. Route SPEC_CORRECTION_NEEDED to the owning clarify gate, never to code; return CONTINUE to the implementation phase with the findings attached.
  6. Never approve or merge; approval and merge stay with the human and the deploy phase.

Step contract

Stepphase_typeoutput_typereads_fromartifact
verifyverifyfindingstest, code—
convergeverifydecisionbrief.md—

Gates

This phase's gate is the converge verdict — a decision gate, not a mechanical red/green gate (the mechanical gates bind the build steps in mission-implement).

  • DONE — the acceptance criteria are met and the quality threshold is reached.
  • CONTINUE — in-scope gaps remain; the findings return to implementation and the circuit breaker applies.
  • SPEC_CORRECTION_NEEDED — a criterion is unmeasurable or the scope conflicts; the verdict routes to the owning clarify gate, never to code.

Boundaries

  • No worktree: isolation belongs to the orchestrator; this skill works in the tree it is handed.
  • No lease: never acquire, renew or release a run lease.
  • No tracker writes: no comments, labels, status transitions, or MR/PR creation.
  • No merge or approval: this skill never approves, merges or ships.
  • Routes back: findings route to the phase that owns the gap; CONTINUE returns to implementation; SPEC_CORRECTION_NEEDED routes to the owning clarify gate, never to code.

Frequently asked questions

What does the Mission Verify AI skill do?

Use when implemented work must be judged against its brief — severity-ranked findings plus one converge verdict of DONE, CONTINUE or SPEC_CORRECTION_NEEDED.

Why use Mission Verify on TypingMind?

Because you install it once and use it with any model. Mission Verify 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 Mission Verify in TypingMind?

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

Which AI models can use Mission Verify?

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 Mission Verify?

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

Is the Mission Verify AI skill free?

Yes. It is published on GitHub by tikalk 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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