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Test Strategy

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nahid-sparktales
test-strategy

Decide what to test and at which level before any tests get written — enumerate failure modes by consequence, give each one the cheapest level that can actually observe it, and name what is deliberately left uncovered. Use when starting testing on a feature or a codebase, when asked for a test plan or why coverage sits where it does, or when a suite is large and still missing bugs. Not for writing the tests themselves, and not for proving a finished change works.

Overview

Publishernahid-sparktales
Repositoryagent-dispatcher
Skill nametest-strategy
Stars
58
Forks
5
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nahid-sparktales on GitHub. Read the source before you install it.

Installation

Install the Test Strategy 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/nahid-sparktales/agent-dispatcher/tree/main/skills/quality/test-strategy
  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/nahid-sparktales/agent-dispatcher.git /tmp/agent-dispatcher
mkdir -p .claude/skills
cp -r /tmp/agent-dispatcher/skills/quality/test-strategy .claude/skills/test-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Test Strategy 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 Test Strategy 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 Test Strategy 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.

Test strategy

Coverage percentage measures which lines ran, not which failures would be caught. A suite can be 90% green and blind to every way the system actually breaks, because tests get written where they are easy to write — pure helpers, config objects, getters — and failures happen at boundaries.

This produces a short written allocation: risks, the level each is tested at, and what is not tested. It does not produce tests.

When this fires

Before writing a batch of tests, when planning a feature's coverage, when a suite is slow or expensive and nobody can say what it buys, or after an escaped bug when the question is why nothing caught it. It does not fire for adding one test to an existing pattern.

Procedure

  1. Enumerate failure modes, not features. For each one: what goes wrong, who notices, and what it costs — corrupted data, money moved twice, a silent wrong number, a page that will not load, a cosmetic slip. Rank by consequence times plausibility. A feature list produces even coverage; a failure list produces useful coverage.
  2. Get the history before trusting your instincts. Bug-fix commits, issue tracker, incident notes, the files that change most often. Where this system has broken before is the best available predictor of where it breaks next, and it is usually not where anyone guessed.
  3. Find the boundaries. Every place data crosses into or out of your control — HTTP, database, queue, filesystem, clock, third party, the user. Most real defects live at boundaries or in the logic that decides which side of one to take.
  4. Assign each risk the lowest level that can actually observe that failure. Lowest is cheapest and most precise — but "lowest" is bounded by observability: a bug that only exists in the interaction between two components cannot be caught by a unit test that mocks the seam it lives in. Choosing a level a mock makes blind is the most common way a green suite misses.
  5. Say what each level is for in this system, in one line each, because the words are used differently everywhere: unit (logic in isolation, no I/O), integration (real adapter against a real dependency — database, HTTP, queue), end-to-end (a whole journey through the running system). Write the definitions you are using; do not argue the pyramid.
  6. Set a budget in seconds, not in counts. How long the suite may take on a developer's machine and in CI. A budget forces the allocation to be real: if every risk lands at the top level, the suite will be slow, flaky and eventually ignored, which is worse coverage than fewer honest tests.
  7. Name what you are choosing not to test, and why. Generated code, framework behaviour, third party internals, exact copy, throwaway spikes, anything whose failure is cheap and obvious. An unlisted gap is an accident; a listed one is a decision.
  8. Name what cannot be tested automatically at all — a payment provider's production behaviour, a physical device, a rendered judgement call — and say what the manual check is and when it runs. Do not silently let the hard parts fall off the plan.
  9. State what a green suite will license you to claim. "These journeys and these boundaries were exercised" is a claim; "the feature works" is not, unless the plan actually covers it. Writing the claim down is what stops tested being reported as verified later.
  10. Check for the untestable design. If a risk cannot be reached at any level without elaborate mocking, that is a finding about the code — a boundary in the wrong place, hidden state, work done in a constructor. Report it as a design finding rather than building the elaborate mock.
  11. Write the allocation down as a table a reviewer can argue with: risk, level, what would have to be true for it to be caught, and its owner if it is manual.

Checklist

  • Failure modes listed with consequence, not a feature list
  • Repository and issue history consulted for where breakage actually happened
  • Boundaries identified and each one assigned a level
  • Every risk placed at the lowest level that can still observe it
  • Level definitions written for this system
  • Runtime budget stated for local and CI
  • Deliberate non-coverage listed with reasons
  • Manual-only checks named with an owner and a trigger
  • The claim a green suite supports is written down
  • Untestable-by-design findings raised rather than mocked around

Failure handling

  • Asked for a coverage percentage target — give the allocation, and say which risks are covered and which are not. A number can be met without touching a single risk on the list.
  • No history available (new code, fresh repository) — say so, and lean on boundaries and on consequence ranking instead. Do not present intuition as evidence.
  • Everything looks high risk — rank anyway, by blast radius. A plan that calls all of it critical allocates nothing.
  • Existing suite is large and unloved — measure before proposing: runtime, failure history, how often a red run found a real bug. Deleting tests is a real deletion of someone else's work: recommend it with the evidence and ask before removing anything.
  • The plan implies changing production code to be testable — that is a legitimate outcome, but it is a separate change with its own review. Name it, do not smuggle it in.

Evidence to report

The risk list with each item's assigned level and the reason that level can see it; the level definitions used; the runtime budget; the explicit not-covered list; the manual checks with owners; and the single sentence saying what a green run of this plan does and does not prove. A plan without a not-covered list is not finished.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Test Strategy AI skill do?

Decide what to test and at which level before any tests get written — enumerate failure modes by consequence, give each one the cheapest level that can actually observe it, and name what is deliberately left uncovered. Use when starting testing on a feature or a codebase, when asked for a test plan or why coverage sits where it does, or when a suite is large and still missing bugs. Not for writing the tests themselves, and not for proving a finished change works.

Why use Test Strategy on TypingMind?

Because you install it once and use it with any model. Test Strategy 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 Test Strategy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nahid-sparktales/agent-dispatcher/tree/main/skills/quality/test-strategy. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Test Strategy?

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 Test Strategy?

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

Is the Test Strategy AI skill free?

Yes. It is published on GitHub by nahid-sparktales 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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