testland/code-change-shape-classifier
Classifies a code change set into four shapes (pure-logic, service-layer, ui-heavy, data-heavy) from file-path and file-content signals, computes the shape distribution over a window of git history, and attaches a relative per-layer test cost model (unit 1x, service 3x, UI 10x) so downstream planning works from one shared input. Produces the classification only: it does not prescribe a target unit:service:UI ratio, does not estimate hours, and does not select which tests to run. Use when a pull request, release branch, or epic needs its change shape labelled before test effort, pyramid balance, or coverage depth is decided.
74
93%
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow runs `git log --name-only`/`git diff ...` to collect changed file paths and may read file content to apply `CONTENT_OVERRIDES`, so it ingests the repository’s (potentially outsider-authored) commit/PR diff text and/or file bodies into the LLM context via the classifier’s runtime inputs.
- Audited
- Security analysis