New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Chatqna API Smoke Test

by open-edge-platform in open-edge-platform/edge-ai-libraries

Validate ChatQnA Core REST APIs from docs/user-guide/api-reference.md using repeatable curl-based smoke tests, runtime-specific endpoint checks (OpenVINO or Ollama), and concise pass/fail evidence.

Apache-2.0Auto-check passedTesting & QA

Install Chatqna API Smoke Test

skills CLI
$ npx skills add open-edge-platform/edge-ai-libraries --skill chatqna-api-smoke-test -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install open-edge-platform/edge-ai-libraries chatqna-api-smoke-test --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/open-edge-platform/edge-ai-libraries.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sample-applications/chat-question-and-answer-core/.github/skills/chatqna-api-smoke-test .claude/skills/chatqna-api-smoke-test && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
chatqna-api-smoke-test
GitHub stars
169
Token cost
~1.6k tokens
SKILL.md length
481 words
Files
5 (incl. scripts)
Skills in repo
29
Repo updated
First seen
Licence
Apache-2.0

At a glance

Validate ChatQnA Core REST APIs from docs/user-guide/api-reference.md using repeatable curl-based smoke tests, runtime-specific endpoint checks (OpenVINO or Ollama), and concise pass/fail evidence.

  • Works in 6 steps: Ensure Deployment Is Running → Preflight and URL Setup → Core Availability → …
  • The user says test APIs
  • SKILL.md covers Environment setup (run first), What This Skill Produces, When to Use and Inputs To Confirm, plus 4 more sections
  • Runs Shell scripts from its folder; calls curl, docker and bash

What it does

Chatqna API Smoke Test is an agent skill from open-edge-platform/edge-ai-libraries. Validate ChatQnA Core REST APIs from docs/user-guide/api-reference.md using repeatable curl-based smoke tests, runtime-specific endpoint checks (OpenVINO or Ollama), and concise pass/fail evidence. Use this skill when the user says "test APIs", "verify endpoint health", "check /chat", "validate docs endpoint", or "smoke test deployment".

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts (for example `benchmark/benchmark.md`, `evals/evals.json` and `evals/trigger-evals.json`).

It sits in Testing & QA, covering QA and bug reports and LLM inference and serving. It works with Ollama. The repository describes itself as: Libraries, microservices, tools, and other reference software, supporting development of performance-optimized Edge AI applications. The licence is Apache-2.0.

When your agent uses it

  • The user says test APIs
  • Verify endpoint health
  • Validate docs endpoint
  • Smoke test deployment

Example prompts

  • “test APIs”
  • “verify endpoint health”
  • “check /chat”
  • “/chatqna-api-smoke-test”

Requirements

  • A Bash shell
  • Docker

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Ensure Deployment Is Running
  2. Preflight and URL Setup
  3. Core Availability
  4. Chat API Check
  5. Runtime-Specific Checks
  6. Document API Checks (Optional)

What it can do on your machine

Read from SKILL.md and the folder at commit cdf860c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • curl
    • docker
    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use curl and docker, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Chatqna API Smoke Test loads about 1.6k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 481 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from open-edge-platform/edge-ai-libraries at commit cdf860c, republished under its Apache-2.0 licence (© open-edge-platform). 481 words, ~1,580 tokens.

Download SKILL.mdSave it as .claude/skills/chatqna-api-smoke-test/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
chatqna-api-smoke-test
description
Validate ChatQnA Core REST APIs from docs/user-guide/api-reference.md using repeatable curl-based smoke tests, runtime-specific endpoint checks (OpenVINO or Ollama), and concise pass/fail evidence. Use this skill when the user says "test APIs", "verify endpoint health", "check /chat", "validate docs endpoint", or "smoke test deployment".
license
Apache-2.0
metadata.version
1.0.0
metadata.tags
chatqna api smoke-test curl openapi health chat documents openvino ollama
<!--
SPDX-FileCopyrightText: (C) 2026 Intel Corporation
SPDX-License-Identifier: Apache-2.0
-->

ChatQnA API Smoke Test

Run practical API checks for ChatQnA Core using the documented endpoints in docs/user-guide/api-reference.md.

Environment setup (run first)

This skill operates on real ChatQnA source files, so the ChatQnA application must be present and commands must run from the app root. Do this before any API validation workflow, whether or not source is already in your workspace.

Run the bundled bootstrap. It searches for an existing ChatQnA checkout by walking up from the current directory and checking the enclosing git repo, then reuses it without re-cloning. Only when no checkout is found does it do a shallow, single-branch, sparse checkout of just sample-applications/chat-question-and-answer-core from main.

It prints the resolved app root on stdout:

bash
# SKILL_DIR is this skill directory. In-repo it is:
# .github/skills/chatqna-api-smoke-test
SKILL_DIR=".github/skills/chatqna-api-smoke-test"
APP_ROOT="$(bash "$SKILL_DIR/scripts/chatqna-bootstrap.sh")"
cd "$APP_ROOT"

Every command below assumes the working directory is this APP_ROOT.

To use a fork/branch or a specific clone path, override these before running the bootstrap script:

  • CHATQNA_REPO_URL
  • CHATQNA_REPO_BRANCH
  • CHATQNA_CLONE_DIR
  • CHATQNA_FORCE_CLONE (set to 1 to force clone)

Codebase root: sample-applications/chat-question-and-answer-core/

What This Skill Produces

  • A runtime-aware API validation report for one scope:
    • Core health and metadata endpoints
    • Chat inference endpoint
    • Document ingestion lifecycle endpoints
    • Runtime-specific endpoints (OpenVINO device APIs or Ollama model APIs)
  • Raw command evidence (curl output + HTTP status) for each check.
  • A concise pass/fail summary with failing endpoint and first actionable next step.

When to Use

  • "Smoke test the API"
  • "Validate /v1/chatqna endpoints"
  • "Check chat endpoint response"
  • "Verify Swagger/OpenAPI endpoints"
  • "Test runtime-specific endpoints for OpenVINO or Ollama"

Inputs To Confirm

Before running checks, confirm or infer:

  1. Base host (HOST_IP, default 127.0.0.1)
  2. Port (default 8102)
  3. Runtime (openvino or ollama, optional but recommended)
  4. Scope (core, chat, documents, runtime, or all; default core)

Base URL:

text
http://<HOST_IP>:8102/v1/chatqna
Show full SKILL.md (208 more words)Show less

Decision Logic

  • If scope is omitted, run core checks first (/health, /model, docs/openapi).
  • If runtime is openvino, include /devices checks.
  • If runtime is ollama, include /ollama-models and optional /ollama-model checks.
  • If user asks for full validation, run all checks.
  • If user asks for non-destructive tests only, avoid POST /documents and DELETE /documents.

Smoke Test Workflow

Run from sample-applications/chat-question-and-answer-core.

1. Ensure Deployment Is Running

If ChatQnA is not already running, start containers before API checks:

bash
# Select runtime profile (choose one)
source scripts/setup_env.sh            # OpenVINO CPU (default)
# source scripts/setup_env.sh -d gpu   # OpenVINO GPU
# source scripts/setup_env.sh -b ollama # Ollama CPU

# Start services
docker compose -f docker/compose.yaml up -d

# Quick readiness check before API probes
docker compose -f docker/compose.yaml ps

If deployment is already running, continue with API smoke tests.

2. Preflight and URL Setup
bash
HOST_IP=${HOST_IP:-127.0.0.1}
BASE_URL="http://${HOST_IP}:8102/v1/chatqna"

echo "${BASE_URL}"
3. Core Availability
bash
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "${BASE_URL}/health"
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "${BASE_URL}/model"
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "http://${HOST_IP}:8102/v1/chatqna/docs"
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "http://${HOST_IP}:8102/v1/chatqna/openapi.json"
4. Chat API Check
bash
curl -sS -X POST "${BASE_URL}/chat" \
  -H "Content-Type: application/json" \
  -d '{"input":"What is Retrieval-Augmented Generation?","stream":false}' \
  -w "\nHTTP_STATUS:%{http_code}\n"
5. Runtime-Specific Checks

OpenVINO:

bash
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "${BASE_URL}/devices"
# Optional device detail probe
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "${BASE_URL}/devices/CPU"

Ollama:

bash
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "${BASE_URL}/ollama-models"
# Optional named model probe
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "${BASE_URL}/ollama-model?model_id=<model-id>"
6. Document API Checks (Optional)

Non-destructive listing:

bash
curl -sS -w "\nHTTP_STATUS:%{http_code}\n" "${BASE_URL}/documents"

Upload and cleanup (run only when user explicitly requests ingestion testing):

bash
curl -sS -X POST "${BASE_URL}/documents" \
  -H "Content-Type: multipart/form-data" \
  -F "files=@./doc1.pdf" \
  -w "\nHTTP_STATUS:%{http_code}\n"

curl -sS -X DELETE "${BASE_URL}/documents?delete_all=true" \
  -w "\nHTTP_STATUS:%{http_code}\n"

Failure Handling

  • HTTP_STATUS is not 2xx:
    • report endpoint, status code, and response body snippet
  • /chat fails:
    • verify request JSON includes non-empty input
  • runtime endpoint mismatch (e.g., /devices on Ollama):
    • note runtime-specific availability from API reference
  • docs/openapi unavailable:
    • verify gateway URL and service readiness via /health

Completion Criteria

  1. Requested scope is executed against the correct base URL.
  2. Runtime-specific checks match selected runtime.
  3. Response includes raw command evidence with HTTP statuses.
  4. Final summary clearly marks pass/fail by endpoint.
  5. For failures, provide one actionable next debugging step.

© open-edge-platform, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts) in sample-applications/chat-question-and-answer-core/.github/skills/chatqna-api-smoke-test of open-edge-platform/edge-ai-libraries.

  • SKILL.md
  • benchmark/benchmark.md
  • evals/evals.json
  • evals/trigger-evals.json
  • scripts/chatqna-bootstrap.sh

Open the folder on GitHubat commit cdf860c

Compare with similar skills

Chatqna API Smoke Test next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Chatqna API Smoke Test compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Chatqna API Smoke Test this skillopen-edge-platform/edge-ai-libraries169—~1.6kAutomated safety check: PassApache-2.0
Release Nyxsthamann/nyx-local-ai133—~609Automated safety check: PassMIT
Forkmindccplugins/awesome-claude-code-plugins970—~868Automated safety check: PassApache-2.0
Release Sample SweepAtmosphere/atmosphere3.8k—~4.2kAutomated safety check: PassApache-2.0
Qwen Mtp GgufR6410418/Jackrong-llm-finetuning-guide1.7k—~1.7kAutomated safety check: PassMIT
Quantized Exportwshobson/agents40k—~2kAutomated safety check: PassMIT

Similar skills

  • Release Nyx

    sthamann/nyx-local-ai

    Ship a new nyx-local-ai release end to end — bump versions consistently, run the quality gates (typecheck, smoke tests, package), install locally, tag and push so CI publishes the installer artifacts.

    133 GitHub stars~609 tokensUpdated 3 mo ago
    Testing & QAAuto-check passed

  • Forkmind

    ccplugins/awesome-claude-code-plugins

    A skill your agent uses when debugging, comparing, or regression-testing LLM / agent calls — when the user wants to capture LLM traffic, see a conversation as a branchable DAG, fork an alternative…

    970 GitHub stars~868 tokensUpdated 1 mo ago
    Testing & QAAuto-check passed

  • Release Sample Sweep

    Atmosphere/atmosphere

    Run the pre-release end-to-end sweep of every user-facing surface — the 33 samples under samples/ (booted from their packaged artifacts and driven in a real browser via chrome-devtools MCP), the…

    3.8k GitHub stars~4.2k tokensUpdated today
    MobileAuto-check passed

  • Qwen Mtp Gguf

    R6410418/Jackrong-llm-finetuning-guide

    Complete agent-ready workflow for Qwen-family MTP or nextn GGUF conversion and release.

    1.7k GitHub stars~1.7k tokensUpdated 3 mo ago
    AI & LLM EngineeringAuto-check passed

  • Quantized Export

    wshobson/agents

    Export a promoted fine-tuned model in the right deployment format — merged safetensors, LoRA-only, GGUF with imatrix, or FP8.

    40k GitHub stars~2k tokensUpdated 4 days ago
    AI & LLM EngineeringAuto-check passed

  • Aider Delegate

    amElnagdy/delegate-skills

    Delegate a coding task to Aider (aider) as a background implementer, then review its diff and land it yourself.

    2.3k GitHub starsUsed in 2 repos~3k tokens
    AI & LLM EngineeringAuto-check passed

More from open-edge-platform/edge-ai-libraries

All 29 skills in this repo

  • Time Series Analytics User

    open-edge-platform/edge-ai-libraries

    Build a new time-series analytics use case on top of the deployed Time Series Analytics microservice — bring it up with Docker Compose (from a repo clone, or by fetching the compose files from…

    169 GitHub stars~3.1k tokensUpdated today
    Auto-check passed

  • Vss Add Nest Module

    open-edge-platform/edge-ai-libraries

    Scaffolds and wires a new NestJS service/module for the Video Search & Summarization sample app's pipeline-manager using the repo's real conventions.

    169 GitHub stars~2.5k tokensUpdated today
    Auto-check passed

  • Chatqna Helm Deploy

    open-edge-platform/edge-ai-libraries

    Deploy Chat Question-and-Answer Core to Kubernetes using Helm (OpenVINO CPU, OpenVINO GPU, or Ollama), including values.yaml configuration, helm install/upgrade, deployment verification, uninstall…

    169 GitHub stars~2.3k tokensUpdated today
    Auto-check passed

  • Generate Changelog

    open-edge-platform/edge-ai-libraries

    Generates or updates CHANGELOG.md by analyzing git commit history between two branches, tags, or revisions in ANY git repository or folder.

    169 GitHub stars~3.1k tokensUpdated today
    Auto-check passed

  • Vss Deploy

    open-edge-platform/edge-ai-libraries

    Deploys and manages VSS through setup.sh and its Docker Compose overlays.

    169 GitHub stars~4.1k tokensUpdated today
    Auto-check passed

  • Vss Deploy Helm

    open-edge-platform/edge-ai-libraries

    A skill your agent uses whenever a developer needs to deploy VSS to Kubernetes, helm install VSS, configure values.yaml for VSS, or run VSS on k8s with GPU/vLLM for the…

    169 GitHub stars~3.8k tokensUpdated today
    Auto-check passed

Works with

Categories

Questions about Chatqna API Smoke Test

What does Chatqna API Smoke Test do?

Validate ChatQnA Core REST APIs from docs/user-guide/api-reference.md using repeatable curl-based smoke tests, runtime-specific endpoint checks (OpenVINO or Ollama), and concise pass/fail evidence. Chatqna API Smoke Test is an agent skill from open-edge-platform/edge-ai-libraries.md using repeatable curl-based smoke tests, runtime-specific endpoint checks (OpenVINO or Ollama), and concise pass/fail evidence.

When should I use Chatqna API Smoke Test?

Chatqna API Smoke Test fits situations like: the user says test APIs; verify endpoint health; validate docs endpoint; smoke test deployment.

How do I install Chatqna API Smoke Test in Claude Code?

Run `npx skills add open-edge-platform/edge-ai-libraries --skill chatqna-api-smoke-test -a claude-code`. Or copy the skill folder (sample-applications/chat-question-and-answer-core/.github/skills/chatqna-api-smoke-test in open-edge-platform/edge-ai-libraries) into .claude/skills/chatqna-api-smoke-test in your project. Claude Code loads it when a task matches its description.

How do I install Chatqna API Smoke Test in Codex?

Run `npx skills add open-edge-platform/edge-ai-libraries --skill chatqna-api-smoke-test -a codex`. Or copy the skill folder (sample-applications/chat-question-and-answer-core/.github/skills/chatqna-api-smoke-test in open-edge-platform/edge-ai-libraries) into .agents/skills/chatqna-api-smoke-test in your project. Codex loads it when a task matches its description.

Can I use Chatqna API Smoke Test in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add open-edge-platform/edge-ai-libraries --skill chatqna-api-smoke-test -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chatqna-api-smoke-test, .gemini/skills/chatqna-api-smoke-test, .github/skills/chatqna-api-smoke-test and .opencode/skills/chatqna-api-smoke-test in your project.

What does Chatqna API Smoke Test need to run?

Going by SKILL.md and its folder, Chatqna API Smoke Test needs a shell for the scripts in its folder and the command-line tools its instructions call (curl, docker and bash). Our summary lists: A Bash shell; Docker.

Does Chatqna API Smoke Test access the network?

SKILL.md contains no URLs. Its commands use curl and docker, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Chatqna API Smoke Test safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Chatqna API Smoke Test use?

Chatqna API Smoke Test is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Chatqna API Smoke Test use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Chatqna API Smoke Test?

Skills that share tags, products or a category with Chatqna API Smoke Test: Release Nyx (sthamann/nyx-local-ai, 133 stars), Forkmind (ccplugins/awesome-claude-code-plugins, 970 stars), Release Sample Sweep (Atmosphere/atmosphere, 3.8k stars) and Qwen Mtp Gguf (R6410418/Jackrong-llm-finetuning-guide, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Chatqna API Smoke Test?

open-edge-platform (a GitHub organization) maintains it in open-edge-platform/edge-ai-libraries, which has 169 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on October 9, 2026.

Source: open-edge-platform/edge-ai-libraries on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.