QVeris — Professional Data and Tool Access for AI Agents

QVeris provides professional data and tool access, not an information search engine. Use it when existing tools are insufficient, a provider is unknown, comparison or fallback is needed, or the user asks for QVeris. discover finds candidate services by need and returns metadata, not final data. call runs the selected service to get structured results.

discover answers "which API tool can do X?" — it cannot answer "what is the value of Y?" To look up facts, answers, or general information, use web_search instead.

Setup: Requires QVERIS_API_KEY from https://qveris.ai.

Credential: Only QVERIS_API_KEY is used. Requests default to https://qveris.ai/api/v1; an audited test run may set QVERIS_BASE_URL=https://api.qveris.cloud/api/v1. The client rejects non-HTTPS and non-QVeris hosts.

Finance CAP requirement: For qveris_finance.* workflows, use the standardized CAP endpoints (/capabilities, /capabilities/{id}, /capabilities/query). When this repository is available, use scripts/qveris_tool.mjs cap-detail/cap-query as the public adapter: it resolves current CAP IDs from the live catalog, validates against live cap-detail, normalizes inputs, retries one transient control-plane fetch failed, performs at most one budget-permitted parameter or explicitly-retryable data retry (--max-attempts 1|2), and records exact observed Trace. Legacy /search plus /tools/execute, generic discover/call, and raw finance tool IDs are not fallbacks. If the standardized CAP runtime is unavailable, report tool_runtime_missing or capability_unavailable instead of selecting a raw provider route.

Invocation Tiers

Check availability in order and use the first working tier:

For standardized finance capabilities, execute POST /api/v1/capabilities/query with capability_id and structured parameters. Do not rediscover or call raw provider routes. The tiers below apply to generic, non-finance tools unless they expose the standardized finance CAP endpoints directly.

Tier 1 — Native tools (when configured): If qveris_discover and qveris_call tools are available in your environment, use them directly — skip all other tiers.

Tier 2 — http_request tool (when configured): Call the QVeris HTTP API directly using the http_request tool (see QVeris API Reference below). Use this tier only if the environment exposes an authorized HTTP tool; availability depends on the host configuration.

Tier 3 — Script execution: Run node {baseDir}/scripts/qveris_tool.mjs cap-list/cap-search/cap-detail/cap-query for standardized CAPs, or discover/call/inspect for legacy generic tools. Use this only when {baseDir}/scripts/ directory is present and the exec tool with node are available.

Tier 4 — Web search: If all tiers above are unavailable, fall back to web_search for qualitative needs.

When and How to Use QVeris

Choosing the Right Tool

Key distinction: QVeris discover finds services by need (e.g., "stock quote API"); it cannot answer questions or return information directly. For factual questions → web_search. For structured data, use QVeris only when an existing connected tool is insufficient or a provider must be found dynamically. Then discover a suitable service and call it. Ask: "Do I need a tool or service, or do I need information?"

Usage Flow

For known standardized capabilities, especially qveris_finance.*, skip legacy discovery and call the CAP directly. Do not switch to a raw finance tool ID when the CAP call fails:

1. Resolve live: cap-detail and cap-query read /capabilities?domain=finance and match the requested logical name or stale punctuation variant to the current canonical CAP ID. Never maintain a hand-written ID map. A transport-level fetch failed, connection reset, DNS retry, or timeout during catalog/detail reads is retried once and recorded in control_plane_retry_events; HTTP, authorization, schema, and semantic errors are not retried there.
2. Preflight live: Read GET /capabilities/{id} on every execution. Allow-list parameters, coerce declared types, fill only documented non-identity required values, normalize .SH/.SZ/.SS and unambiguous six-digit A-share codes, and refuse missing identity, market conflicts, ambiguous exchanges, or a missing parameter schema.
3. Query and retry narrowly: Execute /capabilities/query. Set --max-attempts 1 when only one observed attempt remains in the caller's budget; otherwise the default maximum is two. After a parameter-class failure, retry once by removing an optional input named by the error or by sending required-plus-identity minimal params. Refresh an invalid CAP only when the live catalog now resolves a different ID. Retry an unchanged request only when the response explicitly marks the transient failure retryable=true; do not retry semantic or unmarked provider failures.
4. Use observed output: Read final_params, observed_calls, and qveris_trace from the adapter result. Trace has exactly tool_name, params, status, execution_id, fallback_used, and missing_fields; never reconstruct it from requested params or planned calls.
5. Sanitize recursively: Keep user-facing names as qveris_finance.*; remove provider, route, candidate, failover, credential, raw tool-ID metadata, and provider API URLs from every output surface.

For generic non-standardized, non-finance tools, use the legacy flow:

1. Discover: Find tool candidates for the capability you need. Write the query as an English tool type description (e.g., "stock quote real-time API"). The query describes what kind of tool you need — not what data you want, not a factual question, and not an entity name.
2. Evaluate and call: Select a suitable service using current scope, parameter clarity, coverage, and available signals such as success_rate. Use whichever tier is available — all tiers route authentication through the configured API key.
3. Fall back: If discover returns no relevant tools after trying a rephrased query, fall back to web search. Be transparent about the source.
4. When everything fails: Report which tools were tried and what errors occurred. Training-data values are not live results.

Billing and Audit

QVeris exposes billing in three layers:

• billing_rule: rule-level pricing metadata for a capability.
• billing / pre_settlement_bill: pre-settlement billing for one call.
• usage_history / credits_ledger: final charge outcome and balance movement.

Do not treat legacy cost as the final charge truth. The bundled qveris_tool.mjs displays pre-settlement billing and execution IDs, but does not expose usage-history, ledger, or export commands. Its client module has read-only audit helpers for embedding applications; these are not shell commands.

If the user asks whether a failed call was charged, use an already configured QVeris CLI or MCP audit tool. With the separate @qverisai/cli, run qveris usage --mode search --execution-id <execution_id> --json and inspect charge_outcome; use qveris ledger for balance movements. Do not pass these commands to node scripts/qveris_tool.mjs. If no authorized audit tool is available, provide the execution ID for the user to check in their account history; do not claim to have verified settlement.

For usage and ledger review, protect the Agent context:

• Use the external CLI/MCP summary mode first, then precise filters such as execution_id, charge_outcome, credit amounts, or a date range.
• This skill does not grant filesystem read/write permissions or implement local exports. Only use a separate export/file-analysis workflow when the host already authorizes those operations. Otherwise stay with summaries and filtered queries or ask the user to export the data themselves.

Tool Discovery Best Practices

Discovery Query Formulation

1. Describe the tool type, not the information you want — the query must describe an API capability, not a factual question or entity name:

   • GOOD: "China A-share real-time stock market data API" — describes a tool type
   • BAD: "Zhipu AI stock symbol listing NASDAQ" — this is a factual question, use web_search
   • BAD: "智谱AI 是否上市 股票代码" — this is a factual question in Chinese, use web_search
   • GOOD: "company stock information lookup API" — describes a tool type
   • BAD: "get AAPL price today" — this is a data request, not a tool description
   • GOOD: "stock quote real-time API" — describes a tool type

2. Try multiple phrasings if the first discovery yields poor results — use synonyms, different domain terms, or adjusted specificity:

   • First try: "map routing directions" → Retry: "walking navigation turn-by-turn API"

3. Convert non-English requests to English capability queries — user requests in any language must be converted to English tool type descriptions, not translated literally:

   User request	BAD discover query	GOOD discover query
   "智谱AI是否上市" / "Is Zhipu AI listed?"	"Zhipu AI stock symbol listing" (factual question → use web_search)	"company stock information lookup API"
   "腾讯最新股价" / "latest Tencent stock price"	"Tencent latest stock price" (data request)	"stock quote real-time API"
   "港股涨幅榜" / "HK stock top gainers"	"HK stock top gainers today" (data request)	"hong kong stock market top gainers API"
   "英伟达最新财报" / "Nvidia latest earnings"	"Nvidia quarterly earnings data" (data request)	"company earnings report API"
   "文字生成图片" / "generate image from text"	"generate a cat picture" (task, not tool type)	"text to image generation API"
   "今天北京天气" / "Beijing weather today"	"Beijing weather today" (data request)	"weather forecast API"

Example Discovery Domains

Use these queries to discover candidates. Availability, coverage, and quality depend on the current catalog and each tool's returned metadata:

• Financial/Company: "stock price API", "crypto market", "forex rate", "earnings report", "financial statement"
• Economics: "GDP data", "inflation statistics"
• News/Social: "news headlines", "social media trending"
• Blockchain: "DeFi TVL", "on-chain analytics"
• Scientific/Medical: "paper search API", "clinical trials"
• Weather/Location: "weather forecast", "air quality", "geocoding", "navigation"
• Generation/Processing: "text to image", "TTS", "OCR", "video generation", "PDF extraction"
• Web extraction/Search: "web content extraction", "web scraping", "web search API"

Known Tools Cache

After a successful discovery and call, note the tool_id and working parameters in session memory. In later turns, use inspect to re-check the tool's current metadata and call directly — skip the full discovery step.

Tool Selection and Parameters

Selection Criteria

When discover returns multiple tools, evaluate before selecting:

• Success rate: Prefer success_rate >= 90%. Treat 70–89% as acceptable. Avoid < 70% unless no alternative exists.
• Execution time: Prefer avg_execution_time_ms < 5000 for interactive use. Compute-heavy tasks (image/video generation) may take longer.
• Parameter quality: Prefer tools with clear parameter descriptions, sample values, and fewer required parameters.
• Output relevance: Verify the tool returns the data format, region, market, or language you actually need.
• Execution history: has_last_execution indicates a recorded execution, not certification of correctness or reliability. Evaluate it alongside the returned quality signals.

Before Calling a Tool

1. Read all parameter descriptions from the discovery results — note type, format, constraints, and defaults
2. Fill all required parameters and use the tool's sample parameters as a template for value structure
3. Validate types and formats: strings quoted ("London"), numbers unquoted (42), booleans (true/false); check date format (ISO 8601 vs timestamp), identifier format (ticker symbol vs full name), geo format (lat/lng vs city name)
4. Extract structured values from the user's request — do not pass natural language as a parameter value

Error Recovery

Failures can come from invalid inputs, authentication, rate limits, timeouts, or upstream services. Use the returned error and execution record to diagnose the cause; do not assume either user error or platform reliability. Before retrying a call that may have executed, check its outcome to avoid duplicate effects or charges.

Finance CAP adapter: Parameter validation and one error-guided/minimal or explicitly-retryable transient retry are automatic. Use the adapter's final error, parameter_audit, retry_events, and observed Trace; do not add another blind retry or copy the original parameters into the Trace.

Attempt 1 — Fix parameters: For generic non-finance tools, read the error message. Check types and formats. Fix and retry.

Attempt 2 — Simplify: Drop optional parameters. Try standard values (e.g., well-known ticker). Retry.

Attempt 3 — Switch service: Select another suitable service from discovery results. Call with appropriate parameters.

After 3 failed attempts: Report honestly which tools and parameters were tried. Fall back to web search for data needs (mark the source).

Large Result Handling

Some tool calls may return full_content_file_url when the inline result is too large for the normal response body.

• Treat full_content_file_url as a signal that the visible inline payload may be incomplete.
• Conclusions drawn from truncated_content alone when a full-content URL is present may be incomplete.
• Finance workflows may opt into the shared adapter's approved retrieval path. It accepts only HTTPS from oss.qveris.cloud, refuses redirects, enforces a 10 MiB limit, retries one fetch failed, records host/attempt/size/hash metadata, and then re-applies the requested filters and semantic gates locally.
• The full-content URL and signature are removed before output or artifact storage.
• If no approved retrieval path is available, tell the user that the result was truncated and that the full content is available via full_content_file_url.

QVeris API Reference

Use these endpoints when calling via http_request tool (Tier 2).

Base URL: https://qveris.ai/api/v1

Required headers (on every request):

Authorization: Bearer ${QVERIS_API_KEY}
Content-Type: application/json

Standardized capabilities

Use these endpoints for qveris_finance.* CAP workflows.

GET /capabilities?domain=finance&page=1&page_size=50
GET /capabilities/search?q=end%20of%20day%20bars&domain=finance&limit=5
GET /capabilities/MKT.BARS.EOD
POST /capabilities/query

POST /capabilities/query body:

{
  "capability_id": "MKT.BARS.EOD",
  "parameters": {
    "symbol": "AAPL",
    "start_date": "2026-01-01",
    "end_date": "2026-01-03"
  },
  "strategy": "best",
  "search_id": "optional-from-search"
}

Response contains success, execution_id, capability_id, data, elapsed_time_ms, cost, remaining_credits, and optional _meta. Treat _meta.source_provider, _meta.source_tool_id, and _meta.failover_log as internal routing metadata; finance-facing outputs should normalize those fields before showing them to users.

Discover tools

POST /search
Body: {"query": "stock quote real-time API", "limit": 10}

Response contains search_id (required for the subsequent call) and a results array — each item has tool_id, success_rate, avg_execution_time_ms, and parameters.

Call a tool

POST /tools/execute?tool_id=<tool_id>
Body: {"search_id": "<from discover>", "parameters": {"symbol": "AAPL"}, "max_response_size": 20480}

Response contains result, success, error_message, elapsed_time_ms.

Inspect tool details

POST /tools/by-ids
Body: {"tool_ids": ["<tool_id>"], "search_id": "<optional>"}

Quick Start

Standardized CAP query for finance

Prefer this path for qveris_finance.* workflows:

node {baseDir}/scripts/qveris_tool.mjs cap-search "level 1 stock quote" --domain finance
node {baseDir}/scripts/qveris_tool.mjs cap-detail qveris_finance.mkt_l1_rt
node {baseDir}/scripts/qveris_tool.mjs cap-query qveris_finance.mkt_l1_rt \
  --param symbol=AAPL \
  --safe-json

Equivalent HTTP call:

{
  "method": "POST",
  "url": "https://qveris.ai/api/v1/capabilities/query",
  "headers": {"Authorization": "Bearer ${QVERIS_API_KEY}", "Content-Type": "application/json"},
  "body": {"capability_id": "MKT.L1.RT", "parameters": {"symbol": "AAPL"}, "strategy": "best"}
}

Tier 1 — Native tools (if available)

Use qveris_discover and qveris_call directly when present in your tool list.

Tier 2 — http_request tool

Step 1 — Discover:

{
  "method": "POST",
  "url": "https://qveris.ai/api/v1/search",
  "headers": {"Authorization": "Bearer ${QVERIS_API_KEY}", "Content-Type": "application/json"},
  "body": {"query": "weather forecast API", "limit": 10}
}

Step 2 — Call (use tool_id and search_id from step 1):

{
  "method": "POST",
  "url": "https://qveris.ai/api/v1/tools/execute?tool_id=openweathermap.weather.execute.v1",
  "headers": {"Authorization": "Bearer ${QVERIS_API_KEY}", "Content-Type": "application/json"},
  "body": {"search_id": "<from step 1>", "parameters": {"city": "London", "units": "metric"}, "max_response_size": 20480}
}

Tier 3 — Script execution (if {baseDir}/scripts/ is present)

node {baseDir}/scripts/qveris_tool.mjs discover "weather forecast API"
node {baseDir}/scripts/qveris_tool.mjs call openweathermap.weather.execute.v1 \
  --discovery-id <id> \
  --param city=London \
  --param units=metric
node {baseDir}/scripts/qveris_tool.mjs inspect openweathermap.weather.execute.v1

Quick Reference

Self-Check (before responding)

• For qveris_finance.*, am I using /capabilities/query or cap-query first? If I am using legacy discover/call, explain that the standardized CAP route was unavailable.
• Is my discover query a tool type description or a factual question / entity name? → If it contains specific company names, "is X listed?", or "what is Y?" — use web_search instead. Discover finds tools, not information.
• Am I about to state a live number or need an external capability? → Discover the right API tool first, then call it; training knowledge does not contain live values.
• Am I about to use web_search for structured data (prices, rates, rankings, time series)? → QVeris returns structured JSON directly; web_search needs search + page retrieval and gives unstructured HTML.
• Am I about to give up or skip QVeris because it failed earlier? → Re-engage. Inspect the returned error and execution outcome. Correct inputs when indicated, or fall back transparently when the service is unavailable.
• Did the call result include full_content_file_url? → Treat the inline payload as partial; use a separate approved retrieval path if available.

Common Mistakes