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Qveris Cli

Organization
QVerisAI
qveris-cli

Use QVeris CLI to find and call third-party professional data and tools when existing tools are insufficient, a provider is unknown, comparison or fallback is needed, or the user requests QVeris.

Overview

PublisherQVerisAI
Repositoryqveris-agent-toolkit
Skill nameqveris-cli
Stars
262
Forks
25
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 QVerisAI on GitHub. Read the source before you install it.

Installation

Install the Qveris Cli 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/QVerisAI/qveris-agent-toolkit/tree/main/skills/qveris-cli
  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/QVerisAI/qveris-agent-toolkit.git /tmp/qveris-agent-toolkit
mkdir -p .claude/skills
cp -r /tmp/qveris-agent-toolkit/skills/qveris-cli .claude/skills/qveris-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Qveris Cli 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 Qveris Cli 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 Qveris Cli 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.

Quick first run

New to QVeris? With your QVERIS_API_KEY set (create one at qveris.ai), init is a client-side first-call wizard: auth, discover, inspect, a real call, and exact usage/ledger commands to reconcile billing. It is not a server-side aggregate API.

bash
export QVERIS_API_KEY="sk-..."
npx @qverisai/cli init

Re-run anytime with --query "..." to target a different capability, or --dry-run to validate without consuming credits. Once you've seen the loop, the commands below are the day-to-day surface.

Commands

bash
# Discover tools by capability
qveris discover "weather forecast API" --json --limit 10

# Call after selecting result 1 because its contract matches these exact fields
qveris call 1 --params '{"wfo": "BOU", "x": 50, "y": 30}' --json

# Inspect only when selection/request construction needs missing or stale details
qveris inspect 1 --json

# Probe only for parameter validation or a current quote; it does not reserve a price
qveris probe 1 --params '{"wfo": "BOU", "x": 50, "y": 30}' --checks schema,quote --json

# Validate without consuming credits
qveris call 1 --params '{"wfo": "BOU", "x": 50, "y": 30}' --dry-run --json

# Generate production code snippet (curl/python/js) — only on successful calls
qveris call 1 --params '{"wfo": "BOU", "x": 50, "y": 30}' --codegen curl

Always use --json for structured output.


Response Size

Default: 4KB (TTY) / 20KB (piped/--json). Use --max-size -1 for unlimited. Large responses are auto-truncated with a download link for the full result.


Session Mechanism

The CLI saves the last Discover ID, query, endpoint, and result summaries for 30 minutes. This supports numeric indices and real discovery attribution; it is not semantic routing memory or a complete schema cache. A new Discover replaces the indices. Use qveris history --clear to clear it.

Build parameters from the selected capability's current contract and the user's current request. An explicit empty contract is a zero-parameter tool; an omitted contract requires Inspect. Do not copy sample business values, drop required/enum/one-of constraints, or reuse a previous entity/date value.

For provider comparison, Inspect every candidate when current scope or a complete contract must be confirmed; a Discover summary is not confirmation. Probe every candidate when the comparison requires a current quote. Reuse may preserve an exact route, never business parameters or results: build parameters from the current request, and make a fresh Call for current, latest, today, or other time-sensitive data.


Discover Query Formulation

Describe tool capability, not data you want.

User requestWrongCorrect
"Nvidia earnings""Nvidia earnings""company earnings report API"
"Beijing weather""Beijing weather today""weather forecast API"
"BTC price""what is BTC price""cryptocurrency price API"

Always query in English.


Tool Selection

Choose among connected tools and QVeris by task fit, data quality/freshness, cost, user constraints, and call overhead. Use QVeris when a capability is missing, the provider is unknown, comparison/fallback is needed, or the user requests it. Within Discover results, consider contract fit, provider/coverage constraints, quality, latency, and cost; do not select the first result solely by rank.


Error Recovery

Only retry when the response proves execution did not occur.

  1. For a definite validation failure, fix parameters from the current contract or request missing input.
  2. Drop optional parameters only if doing so preserves the user's requested meaning.
  3. Switch to another compatible result only if provider, coverage, cost, and authorization constraints still hold.

Do not repeat a paid or side-effecting Call after a timeout, network failure, or unknown execution outcome. Report the uncertainty and audit by execution_id when available.

Frequently asked questions

What does the Qveris Cli AI skill do?

Use QVeris CLI to find and call third-party professional data and tools when existing tools are insufficient, a provider is unknown, comparison or fallback is needed, or the user requests QVeris.

Why use Qveris Cli on TypingMind?

Because you install it once and use it with any model. Qveris Cli 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 Qveris Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/QVerisAI/qveris-agent-toolkit/tree/main/skills/qveris-cli. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Qveris Cli?

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 Qveris Cli?

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

Is the Qveris Cli AI skill free?

Yes. It is published on GitHub by QVerisAI 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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