qveris-professional-da…
Find and retrieve current professional data through the connected QVeris connector. Use when the user needs structured external…
Access third-party professional data and tools through QVeris: find services, review supported scope when needed, call them, and generate production REST code. Use when existing tools are insufficient, a provider is unknown, comparison or fallback is needed, or the user requests
$ npx -y skills add QVerisAI/qveris-agent-toolkit --skill qveris --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/qverisContext preview
The summary Claude sees to decide when to auto-load this skill.
Access third-party professional data and tools through QVeris: find services, review supported scope when needed, call them, and generate production REST code. Use when existing tools are insufficient, a provider is unknown, comparison or fallback is needed, or the user requests
name: qveris description: "Access third-party professional data and tools through QVeris: find services, review supported scope when needed, call them, and generate production REST code. Use when existing tools are insufficient, a provider is unknown, comparison or fallback is needed, or the user requests QVeris."
For more detailed discovery query formulation, tool selection criteria, parameter handling, and error recovery, see the [Agent Guidelines](https://github.com/QVerisAI/qveris-agent-toolkit/blob/main/agent/GUIDELINES.md).
Choose among connected tools and QVeris using task fit, data quality/freshness, cost, user constraints, and call overhead. Use QVeris when at least one of these is true:
Local computation and transformations do not need QVeris. For qualitative pages, tutorials, or factual browsing, use an available browsing tool unless structured API data or provider routing is required.
When external functionality is needed, follow this two-phase workflow. Discover, Inspect, Probe, and Call are independent protocol actions, not four mandatory steps.
1. Identify the service or data/tool access the user needs. 2. Call `discover` with a **functionality description** (not parameter names). Request only a few results unless comparison is necessary. 3. If the best discovery result already includes enough parameter guidance and cost information, call it directly with `call`, passing parameters via `params_to_tool`. 4. Use `inspect` only when selection or valid request construction depends on contract details omitted by Discover, multiple candidates need comparison, or a host-managed metadata entry needs refreshing. 5. Use `probe` only when parameters need validation, a current quote is needed for a budget decision, or the user explicitly wants a preflight. Probe is not a prerequisite for Call; its quote is not a price reservation or user authorization. 6. Repeat or broaden the discovery query only if no suitable capability is found or a safe fallback is needed.
Optimize for the shortest safe path:
Do not assume generic MCP or stateless SDK clients provide semantic route memory. Preserve the selected result's real `search_id` within the active flow. If the host explicitly exposes a current known-capability entry, reuse it only for an exact capability intent and unchanged provider/coverage constraints; rebuild all business parameters from the current request.
Inspect when that host entry's contract is missing or stale. Discover again when intent, coverage, provider, authorization, or endpoint context changes; the entry expires; the capability is unavailable; or comparison/fallback is needed. Never invent `search_id`, reuse another discovery's attribution, or cache credentials, sensitive user values, or business results.
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.
An explicit empty parameter contract means the tool takes no parameters. A missing contract is not equivalent: Inspect it or request the missing business input before Call. Preserve required, enum, and alternative/one-of constraints. Never copy sample values as if they were the user's request.
Compatibility note: legacy MCP names `search_tools`, `get_tools_by_ids`, and `execute_tool` remain deprecated aliases only. Prefer `discover`, `inspect`, and `call` in all new workflows.
QVeris separates pricing rules, pre-settlement billing, and final settlement:
When the user asks whether a failed call was charged, do not infer from `cost` alone. Query `usage_history` with the `execution_id` and inspect `charge_outcome`.
Use context-safe audit patterns:
Once a suitable tool is identified, generate code that calls the QVeris REST API directly. Do **not** reuse the MCP tool-call result — produce standalone code the user can run.
Bring professional data and tools to the AI you already use: open-source MCP, CLI, SDKs, skills, and docs to find services, call them, and audit usage.
Find and retrieve current professional data through the connected QVeris connector. Use when the user needs structured external…
Use QVeris CLI to find and call third-party professional data and tools when existing tools are insufficient, a provider is…