accessibility-gate
Use as a pass/fail gate on any diff with a user-facing surface — by code-reviewer during review, by qa-engineer during the test pass, and by any IC before…
Use when turning store reviews, support threads, crash clusters or feedback into ranked product findings — by data-analyst post-launch, and by product-researcher when existing user evidence is the question. A review-mining pass, not a standing role.
$ npx -y skills add vmobifystudio/app-dev-team --skill support-mining --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/support-miningContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when turning store reviews, support threads, crash clusters or feedback into ranked product findings — by data-analyst post-launch, and by product-researcher when existing user evidence is the question. A review-mining pass, not a standing role.
name: support-mining description: Use when turning store reviews, support threads, crash clusters or feedback into ranked product findings — by data-analyst post-launch, and by product-researcher when existing user evidence is the question. A review-mining pass, not a standing role.
Users describe symptoms, in their own words, having already worked around the problem. This is the pass that turns that into something the board can act on — and the discipline that keeps it from becoming a list of the loudest complaints.
| Source | Good evidence for | Systematically biased toward | |---|---|---| | Store reviews | first-run and pricing friction | the delighted and the furious, never the middle | | Support threads | reproducible defects | users willing to write in — a small, patient minority | | Crash clusters | the truth about stability | devices and OS versions you have most of | | Uninstall / churn signals | where value failed to land | nothing at all about why |
**Name the bias in the report.** A finding from reviews alone is a finding about reviewers.
1. **Cluster by user-described symptom, not by your guess at the cause.** "Photos disappeared" and "lost my edits" may be one defect or three; keep them separate until evidence merges them. 2. **Rank by `frequency × severity × recency`**, and show all three columns. A cluster ranked by volume alone buries the data-loss report mentioned twice. 3. **Attach evidence to each cluster** — verbatim quotes with dates, app version, device and OS where available. A cluster with no verbatim is your paraphrase, and you label it as such. 4. **Separate a defect from a missing feature from a misunderstanding.** All three arrive as "it doesn't work" and they route to three different people. A misunderstanding is a `content-design` finding, not a bug. 5. **Check each cluster against `knowledge/failure-corpus.md`.** A cluster matching a known class that already has a shipped rule is a **recurrence** — the rule did not work, and that is a strictly more valuable finding than the incident.
without one wastes a developer's day.
regressed is how a good release gets rolled back.
A dated `## Support findings` section in `docs/51-bugs.md`: ranked clusters with their three scores, verbatim evidence, the classification (defect · missing feature · misunderstanding · recurrence of FC-NNN), and the proposed owner for each.
Describe your app idea in one line. Get a shipped iOS & Android app. AI App Studio is a team of 30 AI specialists — a CEO, product manager, designers, iOS/Android engineers, a code reviewer, QA, and a release manager — that works like a real software studio.
Repo: vmobifystudio/app-dev-team
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