Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cenconq25/claude-code-app-studio --skill day-one-patchgit clone --depth 1 https://github.com/cenconq25/claude-code-app-studioWrote 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.
[](https://agentmods.dev/skills/cenconq25/claude-code-app-studio/day-one-patch)<a href="https://agentmods.dev/skills/cenconq25/claude-code-app-studio/day-one-patch"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/day-one-patch/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.
<a href="https://agentmods.dev/skills/cenconq25/claude-code-app-studio/day-one-patch"><img src="https://agentmods.dev/badge/skills/cenconq25/claude-code-app-studio/day-one-patch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.01681 |
| Opus 5.5 | $0.00022 | $0.00672 |
| Sonnet 5.5 | $0.00011 | $0.00336 |
| Haiku 4.5 | $0.00006 | $0.00168 |
Grade A, and why
day-one-patch 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Day-One Patch
Between the build that went to certification and the build users see at launch, problems show up — late-breaking telemetry, a cert reviewer finding, a marketing copy change. This skill scopes a focused mini- sprint patch, runs it through QA, and lands it on the user before they even notice the gap.
Phase 1: Source the Patch Scope
Resolve the source build:
--from=<release-tag>-> read that tag.- Otherwise consult
production/releases/release-checklist-*.mdfor the latest release version and use its tag.
Source the candidate patch list from any of:
--bug-list=<paths>-> explicit list.- Recent BUG records filed since the release tag in
production/qa/bugs/. - Recent S1/S2 issues triaged in
production/qa/triage-*.md. - App Store / Play review feedback (if pasted by user).
- Late-breaking telemetry alerts (Sentry / Crashlytics digest).
Render the candidate list with severity, frequency (if known), and origin source.
Phase 2: Filter to Day-One Scope
Apply the day-one bar — only fixes that meet ALL of these qualify:
- Severity S1 or S2.
- Reproducible.
- Fix is small (< 2 days of engineering, ideally < 1).
- Fix is low-risk (touches a small, well-understood area).
- Fix has a regression test plan.
Any candidate failing the bar is either downgraded to a normal sprint,
escalated to /hotfix, or rejected.
Use AskUserQuestion to confirm scope:
question: "Day-one scope candidates (top severity first):"
options:
- "Accept the proposed scope"
- "Add: [user provides]"
- "Drop: [user provides]"
- "Cancel — these are not day-one items"
Phase 3: Risk Assessment
For the agreed scope, run the patch-risk checklist:
- Each fix has a clear blast radius (which features, which user cohort).
- Combined diff stays under [project threshold, default 500 LOC].
- No fix changes the public API surface.
- No fix changes the on-disk data schema.
- No fix touches payment flow without a payments specialist on review.
- No fix touches auth flow without a security review.
- No fix is bundled with a feature change — patch is fixes only.
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.
- 1mo ago First seen · 255 lines · 56 tokens per session scan A ebf6e85d5341
day-one-patch is a skill published in the GitHub repository cenconq25/claude-code-app-studio (42 stars, last pushed 5mo ago), licensed MIT. It adds 56 tokens to every session and 1,681 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 2026-09-03.
Other skills, from other repositories
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
systematic-debugging
Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
cwv-optimizer
Diagnose and fix Core Web Vitals issues on AEM Edge Delivery Services pages. Goes deeper than generic CWV advice by understanding EDS-specific performance patterns including the 100KB LCP budget, E-L-D loading phases, block rendering behavior, and third-party script impact. Produces specific fixes for LCP, CLS, and…
incident-response-incident-response
Coordinate production incident triage, mitigation, investigation, recovery, and follow-up. Use when responding to outages or other incidents that require structured operational coordination.
ci-fixer
CI failures - read error, minimal fix, verify.