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Project Flow Ops

Community
Mark393295827
project-flow-ops

Use when projects or tasks need explicit state, WIP control, ownership, definitions of done, blocker handling, and verified closure.

Overview

PublisherMark393295827
Repositorythird-brain-v7-skills
Skill nameproject-flow-ops
Stars
141
Forks
22
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 Mark393295827 on GitHub. Read the source before you install it.

Installation

Install the Project Flow Ops 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/Mark393295827/third-brain-v7-skills/tree/main/skills/project-flow-ops
  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/Mark393295827/third-brain-v7-skills.git /tmp/third-brain-v7-skills
mkdir -p .claude/skills
cp -r /tmp/third-brain-v7-skills/skills/project-flow-ops .claude/skills/project-flow-ops
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project Flow Ops 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 Project Flow Ops 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 Project Flow Ops 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.

Project Flow Ops

<skill_contract> Project objective, tasks, owners, dependencies, budgets, artifacts, current states, and definitions of done. A WIP-limited project state with ranked work, explicit blockers, bounded actions, and verified closure receipts. Every active item has one owner and observable artifact, and completion is backed by its named fresh verification. <non_goals>Hidden WIP, duplicate ownership, status by intuition, backlog accumulation, or completion without evidence.</non_goals>

Maintain a small, inspectable project state machine: BACKLOG -> ACTIVE -> BLOCKED | COMPLETED. Optimize flow and verified outcomes, not task volume.

Usage Template

Provide: project objective, current tasks, owners, dependencies, time budget, artifacts, and definition of done. Optional: prior review receipts.

Workflow

Normalize each item into {id, objective, owner, state, artifact, definition_of_done, budget, dependencies}. Reject duplicate ownership and distinguish waiting from active execution.

<unknowns_gate>

If an active item lacks an owner, artifact, or observable definition of done, return NEEDS_INPUT. Probe the ambiguity with the largest impact on scheduling; do not guess priority from wording alone.

</unknowns_gate>

  1. Rank work by objective impact, urgency, dependency leverage, and cost of delay.
  2. Limit ACTIVE to one or two items per owner.
  3. Decompose the selected item until one bounded action can produce a reviewable artifact.
  4. For a blocker, record owner, missing condition, evidence, next probe, and review time; move independent work forward.
  5. Run the verification named in the definition of done.
  6. Move to COMPLETED only with a fresh receipt; otherwise keep ACTIVE or BLOCKED.
  7. At review, remove stale backlog items and state the next constraint.

Check state-transition legality, WIP limits, ownership, artifact existence, and completion evidence. Use an independent check for consequential deliverables. If verification fails, reopen the item with the failure evidence and smallest corrective action.

<state_contract>

Persist {run_id, status, attempt, budget, evidence, unknowns, last_error, next_action} plus project objective, task ledger, dependency map, WIP count, transition history, and receipts. Transitions are append-only events; current state is derived from the latest valid event.

</state_contract>

Failure Protocol

  • NEEDS_INPUT: ownership, priority boundary, or definition of done is missing.
  • BLOCKED_DEPENDENCY: execution cannot continue; preserve the blocker contract and review time.
  • VERIFY_FAILED: the artifact fails its named check; reopen rather than relabel completion.
  • NO_PROGRESS: two reviews produce no new evidence; reduce scope, change strategy, or escalate.
  • BUDGET_STOP: stop active work, persist state, and report the highest-value next action.

Output Contract

Return status, result (project board and transition decisions), evidence (artifacts and receipts), unknowns, and next_action with owner and review time.

Edge Cases

  • Everything is marked urgent: use cost of delay and dependency leverage, then force one explicit tradeoff.
  • A task is 90% complete but verification is unavailable: keep it active or blocked; never infer the final 10%.

Success Metrics

  • Active WIP remains within the declared limit.
  • Every completed task has an artifact and fresh verification receipt.
  • Blocked work names an owner, next probe, and review time.

Quality Gates

  • Every active task has one owner and bounded budget.
  • State transitions are legal and traceable.
  • Completion evidence is fresh and objective.
  • The next constraint is explicit after each review.

</skill_contract>

Frequently asked questions

What does the Project Flow Ops AI skill do?

Use when projects or tasks need explicit state, WIP control, ownership, definitions of done, blocker handling, and verified closure.

Why use Project Flow Ops on TypingMind?

Because you install it once and use it with any model. Project Flow Ops 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 Project Flow Ops in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/project-flow-ops. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Project Flow Ops?

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 Project Flow Ops?

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

Is the Project Flow Ops AI skill free?

Yes. It is published on GitHub by Mark393295827 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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