ontario-data-mcp: Skill for Claude Code

.claude/skills/generating-smoke-tests/SKILL.md

generating-smoke-tests is a skill for Claude Code from sprine/ontario-data-mcp. It costs 44 tokens per session (2,239 once invoked), scanned A, original, MIT.

A procedure for creating and running temporary live tests against Ontario public data services. A smoke test is a short end-to-end check that confirms key parts of a system work together.

In plain words
What is it for?
Release checks, post-refactoring verification, and testing connectivity to Ontario, Toronto and Ottawa data APIs.
Why use it?
It checks real connections and multiple server tools after changes, so wiring or integration problems are found before a release.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is sprine/ontario-data-mcp's own configuration. It tells Claude Code how to work on ontario-data-mcp itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ontario-data-mcp configures →

Reuse

Borrowing it

Nothing to install: this file belongs to sprine/ontario-data-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/sprine/ontario-data-mcp/main/.claude/skills/generating-smoke-tests/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/sprine/ontario-data-mcp

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for generating-smoke-tests

README.md
[![agentmods](https://agentmods.dev/badge/skills/sprine/ontario-data-mcp/generating-smoke-tests/github.svg)](https://agentmods.dev/skills/sprine/ontario-data-mcp/generating-smoke-tests)
Your own site
<a href="https://agentmods.dev/skills/sprine/ontario-data-mcp/generating-smoke-tests"><img src="https://agentmods.dev/badge/skills/sprine/ontario-data-mcp/generating-smoke-tests/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for generating-smoke-tests

Your own site · 80×15
<a href="https://agentmods.dev/skills/sprine/ontario-data-mcp/generating-smoke-tests"><img src="https://agentmods.dev/badge/skills/sprine/ontario-data-mcp/generating-smoke-tests.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,239 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00044 $0.02239
Opus 5.5 $0.00018 $0.00896
Sonnet 5.5 $0.00009 $0.00448
Haiku 4.5 $0.00004 $0.00224

Measured 2mo ago against content hash 5a602ba3b0f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

generating-smoke-tests scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/generating-smoke-tests/SKILL.md · 209 lines

How it starts

The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generating Smoke Tests

Generate a temporary Python smoke-test script that exercises multiple MCP tools against the live Ontario, Toronto, and Ottawa data APIs, run it, verify all assertions pass, then clean up.

When to Use

  • During the release process (after unit tests pass, before version bump)
  • After refactoring tool code, server wiring, or lifespan/context changes
  • When verifying end-to-end connectivity to data.ontario.ca

Instructions

1. Generate the smoke test script

Write a file called smoke_test.py in the project root. The script must:

  1. Discover the latest dataset dynamically — fetch https://data.ontario.ca/feeds/dataset.atom, parse the first <entry> to extract the dataset UUID from its <id> tag (format: https://data.ontario.ca/dataset/{uuid})
  2. Set up real dependencies — httpx.AsyncClient, CKANClient, CacheManager with a temp DuckDB path
  3. Mock only the FastMCP context — use the pattern from tests/conftest.py:
    from unittest.mock import AsyncMock, MagicMock
    from ontario_data.portals import PORTALS
    ctx = MagicMock()
    ctx.report_progress = AsyncMock()
    ctx.lifespan_context = {
        "http_client": http_client,
        "portal_configs": PORTALS,
        "portal_clients": {},
        "cache": cache,
    }
    
  4. Access tools via the FastMCP API: tool = await mcp.get_tool("tool_name") then await tool.fn(...)
  5. Exercise this tool chain (each step asserts success before continuing):
    • Ontario: search_datasets(query="ontario", portal="ontario") — assert total_count > 0
    • Ontario: get_dataset_info(dataset_id=<uuid from feed>) — assert returns id or name
    • Ontario: download_resource(resource_id=...) — pick first datastore-active resource; if none found, try the next feed entry (up to 5) until one with a datastore-active resource is found
    • Ontario: query_cached(sql=...) — SELECT COUNT(*) as cnt from the cached table
    • Ontario: cache_info() — assert table_count > 0
    • Toronto: search_datasets(query="toronto", portal="toronto") — assert total_count > 0
    • Ottawa: search_datasets(query="ottawa", portal="ottawa") — assert total_count > 0
  6. Clean up — close the httpx.AsyncClient; CacheManager uses short-lived connections and needs no close
  7. Print progress — each step prints a summary line prefixed with two spaces
  8. Print "All smoke tests passed!" on success

Read the full file on GitHub · 209 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 209 lines · 44 tokens per session scan A 5a602ba3b0f0

Subscribe to this mod's changes

generating-smoke-tests is a skill published in the GitHub repository sprine/ontario-data-mcp (1 stars, last pushed 12d ago), licensed MIT. It adds 44 tokens to every session and 2,239 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

generating-smoke-tests compared with skills from other repositories

generating-smoke-tests next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
generating-smoke-testssprine/ontario-data-mcpSkill112d agoMITA44Claude Code
verify-omnigentomnigent-ai/omnigentSkill11kyesterdayApache-2.0A100Claude Code, Codex
test-masterJeffallan/claude-skillsSkill12k7d agoMITA104Claude Code
eval-dataset-designbojieli/ai-agent-bookSkill57k29d agoApache-2.0A138Claude Code, Codex
dogfoodcallstack/agent-deviceSkill5.3kyesterdayMITA55Claude Code
cua-driverdavidondrej/skillsSkill4.3k3d agoMITA68Claude Code, Codex
test-warp-uiwarpdotdev/warpSkill66kyesterdayAGPL-3.0A55Claude Code