Common Operator Profile logo

Common Operator Profile

Community
HoangNguyen0403
common-operator-profile

Infer the requesting operator's technical fluency from message content (never ask directly) and adapt register — business, hybrid, or technical — across SDLC workflow output. Use when starting sdlc, brainstorm-feature, plan-feature, verify-work, publish-notes, or session-report, or whenever a request's phrasing signals a non-technical or cross-stack operator.

Overview

PublisherHoangNguyen0403
Repositoryagent-skills-standard
Skill namecommon-operator-profile
Stars
573
Forks
166
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 HoangNguyen0403 on GitHub. Read the source before you install it.

Installation

Install the Common Operator Profile 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/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/common/common-operator-profile
  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/HoangNguyen0403/agent-skills-standard.git /tmp/agent-skills-standard
mkdir -p .claude/skills
cp -r /tmp/agent-skills-standard/.agents/skills/common/common-operator-profile .claude/skills/common-operator-profile
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Common Operator Profile 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 Common Operator Profile 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 Common Operator Profile 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.

Operator Profile

Priority: P0 (CRITICAL)

1. Infer, Never Ask

Classify the requesting operator into exactly one tier from message content alone. Do not ask "how technical are you?" or similar — inference only. Treat the tier as internal response context: continue with the requested work in that register. Never return only business, hybrid, or technical as the answer.

TierSignal
technicalNames files, branches, PRs, diffs, frameworks, stack traces, ticket IDs, or existing code.
hybridFluent in one stack, asks definitional questions about another ("I know Laravel, new to NestJS").
businessOutcome/goal language only, no code or file artifacts, business vocabulary ("customers", "revenue", "an app that tracks...").

Default to hybrid when ambiguous. Revise silently as new evidence arrives in the same session; never re-ask. The profile is decided once per session and carried forward as operator_profile in every Handoff Payload so downstream workflows never re-infer it.

An explicit profile=business|hybrid|technical invocation argument always overrides inference.

For traceable workflow output, name the inferred register once when it matters (for example, Profile: business or Profile: technical) and then continue with the substantive answer. Never return only the label. File paths, requirement IDs, and test references such as prd-checkout.md and checkout.spec.ts are technical signals even when the request is otherwise brief.

2. Register Rules Per Tier

  • business: Lead every response with a plain-language outcome summary (what changes for the business, no jargon). Move file paths, IDs, commands, and stack detail into a trailing "Technical Appendix" the operator can skip. Frame Blocking Questions as business choices, each with a recommended default answerable by "go with your suggestion." Proxy purely technical decisions (tech stack internals, library choice) without asking — record them as assumptions, not blockers.
  • hybrid: Full technical detail. Define unfamiliar-stack concepts on first use and map them to the operator's declared home stack when known (e.g., map a NestJS Module or Provider to its Laravel equivalent).
  • technical: Terse, full detail, no explanations of standard concepts. If essential artifacts are unavailable, name the exact supplied requirement, file, or test needed; do not replace the task response with a profile label.

3. Proxy-Defaults Rule

For operator_profile=business, workflows with a hard-blocking floor (missing sponsor, missing SMART metric, missing scope fence) must draft a sensible default for each missing item and present them as one confirm-with-default question round instead of returning BLOCKED outright. Only return BLOCKED if the operator rejects the drafted defaults or the workflow cannot obtain operator confirmation.

Use the literal label SMART metric when drafting the measurable success target, and use Profile: technical when file, requirement, or test references establish a technical operator.

Anti-Patterns

  • No upfront skill-level question: never ask the operator to self-classify.
  • No persisted profile config: infer per-session from the message; do not read or write a stored preference file.
  • No jargon-first response for business tier: leading with file paths or command output before the plain-language summary is a violation.

Blocked-request wording

  • If implementation cannot proceed, say clearly that you are unable to implement because required access or inputs were not supplied; do not invent evidence.

Remediation anchors

  • Remediation anchors: business, technical, operator_profile, infer from file and requirement references, continue with explicit assumptions when artifacts are unavailable

Frequently asked questions

What does the Common Operator Profile AI skill do?

Infer the requesting operator's technical fluency from message content (never ask directly) and adapt register — business, hybrid, or technical — across SDLC workflow output. Use when starting sdlc, brainstorm-feature, plan-feature, verify-work, publish-notes, or session-report, or whenever a request's phrasing signals a non-technical or cross-stack operator.

Why use Common Operator Profile on TypingMind?

Because you install it once and use it with any model. Common Operator Profile 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 Common Operator Profile in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/common/common-operator-profile. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Common Operator Profile?

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 Common Operator Profile?

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

Is the Common Operator Profile AI skill free?

Yes. It is published on GitHub by HoangNguyen0403 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇