Bootstrap a Test Suite
Skill:erm-bootstrap-testsuite
Use it when: you have a configuration but little or no Test Suite, or you want more coverage for specific categories.
Example prompt:
“Using allGood ERM, bootstrap a test suite for configuration QU8RSBZL.”
What happens
1
It reads your configuration and existing suite
The assistant reads your categories, then pages through every existing test case so it doesn’t duplicate one. If you pointed it at a draft, it asks whether to start that draft’s suite from scratch or copy the live suite over first.
2
It plans what's missing
It compares your categories to your cases and decides what to add, what to update, and what to leave alone. If it can’t cover everything at once, it covers categories with no flags first, since those are real human replies, then Spam, Bounce, Out of Office, and Auto Response. It skips the catch-all Other category.Each category gets at least one categorize test. Categories with extract fields also get a categorize and extract test whose email contains real values for those fields.
3
You approve the plan
You see the new cases it proposes. For any case it wants to change, you see the exact old and new values. Nothing is written until you approve.
4
It creates the cases and runs the suite
It adds and updates the cases, runs the suite, and reports the real results, including whether the new cases passed. A new case that fails right away often means either the email wasn’t clear-cut, or it exposed a real gap in a category definition. The assistant flags both.
Improve accuracy
Skill:erm-learning-loop
Use it when: you already have a Test Suite and want to improve how well replies are categorized and extracted.
Example prompt:
“Using allGood ERM, run the learning loop on configuration QU8RSBZL and show me what’s failing.”
This needs an existing Test Suite. If you don’t have one, bootstrap it first.
What happens
1
Evaluate
It runs the whole suite and tells you total, passed, failed, errored, not run, and overall accuracy.
2
Rank failures by how much they matter
Not every wrong answer costs the same. The assistant groups your categories by their flags and ranks each failure:
You get this as a table, worst first, and the assistant digs into the 🔴 and 🟡 rows by reading actual examples to work out why.
3
Check coverage
A category with one or two test cases can show 100% and still be essentially untested. The assistant counts cases per category and flags thin ones. If coverage is the real problem, it sends you back to bootstrap rather than rewriting a category based on too little evidence.
4
Review the proposed changes
For every field it wants to change, you see the exact old text and the exact new text. Nothing changes until you approve those specific edits. You can word a fix differently.
5
It edits a draft, never your live configuration
It creates a draft if there isn’t one, copies your Test Suite onto it (a new draft starts empty), and applies the approved edits.
6
It re-runs the suite and repeats
It re-runs the suite on the draft and compares accuracy and failures to the previous run. If failures remain or new ones appeared, it goes round again. There’s no fixed number of rounds.
What you get at the end
- The full diff: every field changed across every round, as old and new text
- The accuracy trend: starting accuracy, accuracy after each round, and the final number
- A pointer to review the draft in the web app. The assistant stops there. Publishing is always your decision.
Using the skills
- Claude Code
- Claude Desktop or ChatGPT
The skills ship in the allGood ERM plugin along with the connection to the ERM MCP. Ask your allGood contact for the plugin for your environment, then start Claude Code with it:Claude Code asks you to sign in to allGood the first time it connects.