Agent skill

Fix Nightly Failures

by Mentra-Community in Mentra-Community/MentraOS

Diagnose an ongoing or finished Mentra nightly suite, group demonstrated shared failures, implement fixes, and carry PRs through independent Codex review and merge.

Apache-2.0Auto-check passedDevOps & Cloud

Install Fix Nightly Failures

skills CLI
$ npx skills add Mentra-Community/MentraOS --skill fix-nightly-failures -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Mentra-Community/MentraOS fix-nightly-failures --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Mentra-Community/MentraOS.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/fix-nightly-failures .claude/skills/fix-nightly-failures && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
fix-nightly-failures
GitHub stars
2.4k
Token cost
~2.8k tokens
SKILL.md length
1,494 words
Files
3 (incl. references)
Skills in repo
11
Repo updated
First seen
Licence
Apache-2.0

At a glance

Diagnose an ongoing or finished Mentra nightly suite, group demonstrated shared failures, implement fixes, and carry PRs through independent Codex review and merge.

  • A chat is pointed at a nightly suite
  • SKILL.md covers Start from the suite, Preserve independent execution, Diagnose and group on evidence and Implement and finish the PR…, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Deployment and a new full suite are separate work

What it does

Fix Nightly Failures is an agent skill from Mentra-Community/MentraOS. Diagnose an ongoing or finished Mentra nightly suite, group demonstrated shared failures, implement fixes, and carry PRs through independent Codex review and merge. Use when a chat is pointed at a nightly suite; deployment and a new full suite are separate work.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/operations.md`).

It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: MentraOS is the leading smart glasses OS. See live captions, stream your view, talk to AI, and capture photos hands-free on compatible glasses. The licence is Apache-2.0.

When your agent uses it

  • A chat is pointed at a nightly suite
  • Deployment and a new full suite are separate work

Example prompts

  • “/fix-nightly-failures”

What it can do on your machine

Read from SKILL.md and the folder at commit bc626e0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Fix Nightly Failures loads about 2.8k tokens when it runs, and up to ~5.6k if it reads all its reference files. Until then it costs about 71 tokens; SKILL.md has 1,494 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Mentra-Community/MentraOS at commit bc626e0, republished under its Apache-2.0 licence (© Mentra-Community). 1,494 words, ~2,800 tokens.

Download SKILL.mdSave it as .claude/skills/fix-nightly-failures/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
fix-nightly-failures
description
Diagnose an ongoing or finished Mentra nightly suite, group demonstrated shared failures, implement fixes, and carry PRs through independent Codex review and merge. Use when a chat is pointed at a nightly suite; deployment and a new full suite are separate work.

Fix nightly failures

Own the source repair loop: evidence → diagnosis → fix → PR → independent review → required checks → merge → final report. A standalone chat can start from an ongoing or finished suite. Do not require a continuously running coordinator. Carry each fix through targeted verification when the user requests suite repair and the required source/API is available. Approved merged source is a milestone; record deployment prerequisites while continuing other repairs. Framework deployment, a new full-catalog suite and Slack delivery are separate tasks unless authorized. A merged fix does not make the original suite pass.

Start from the suite

Accept a suite URL, suite ID or occurrence/workflow ID, plus any branch, repository, verification or merge constraints. Resolve these to the canonical occurrence and stable result URL; ask only for an identifier or access genuinely needed to read it. Discover provisioned tools, APIs and authentication using operations. Do not require this chat's history, a particular host, coordinator or source SHA.

Example launch:

$fix-nightly-failures <suite URL> — Diagnose failures while remaining members run, fix their owning repositories, open PRs, run codex-pr-review, address findings and merge after approval and required checks. Report conclusions and verification. Do not deploy or start another full suite.

Record the complete selected member list, status, frozen harness/definition revisions and exact app/firmware publication. GitHub accepting a dispatch, an active chat or successful teardown does not prove device execution or a pass. Keep unavailable observations unknown; do not substitute today's build or copy an old success forward.

Preserve independent execution

Diagnose failures as they arrive and let other suite members continue. Ordinary setup, test or teardown failures do not justify cancelling the suite. Let the controller clean the failed run and repair its lane through normal operations; verify the actual repair invocation, conclusion and accepted resume or out-of-service decision. Healthy lanes continue independently.

Separate the original test outcome from later machine repair, cleanup and publication errors. Repairing machine state does not repair source or change the original verdict. If a global framework fault prevents useful execution, diagnose it and use normal operations within the current cancellation authority. Never force-release hardware, edit controller SQLite, change catalog toggles or weaken assertions to manufacture green. Keep live source/configuration unchanged while accepted work depends on them; this skill does not perform deployment.

Diagnose and group on evidence

Keep one small durable ledger in existing task state: routine/run, failing phase/step, original error and evidence links, exact provenance, classification, causal group and supporting evidence, existing fix/job, PR/head/review, next action and verification result. Fetch the first useful framework result and setup/teardown journal before expanding into screenshots, recordings or command logs.

Classify app, routine, framework, machine/fixture state or unknown on evidence. Compare the failing source with current source before fixing it. Reuse the relevant diagnosis mechanics in fix-routine-failure; this suite's completion boundary takes precedence over that skill's deployment/rerun loop.

Group failures when evidence demonstrates the same cause in a shared provider or action at compatible source/build and triggering conditions. Matching wording alone is insufficient. A suspected shared cause can have one diagnosis owner, but keep it provisional and split when evidence differs. Preserve every member's original outcome; grouping never makes an unverified member pass.

Use one coherent fix for a demonstrated cause. Inspect existing PRs, merged fixes and compatible authoring jobs before creating more. Do not mechanically create one fix or job per failed routine. If the error lacks diagnostic information, fix the bounded, redacted observation gap first. Such a PR does not prove the original cause; do not spend hours repeating complete runs to rediscover it.

Implement and finish the PR lifecycle

Source-only investigation and fixes need no lane or activation receipt. Work in a clean isolated worktree from the current destination branch, retaining the failure's channel provenance: dev → dev, staging → staging, an open PR → its recorded repository/branch and base. Reuse existing relevant work. Keep routine behavior in routines/, shared mechanics in framework providers, and ownership or repair in orchestration. Follow repository guidance and proven actions; avoid new compatibility paths, runners or arbitrary sleeps.

Run meaningful source checks, open a focused PR with diagnosis and validation, and use select-pr-routines for applicable coverage. Label product app fixes bug:app, wrong routine actions/expectations/fixtures bug:routine, and shared execution/orchestration/recording/infrastructure bug:framework; use multiple labels only for multiple corrected components, never bug:harness. A routine's Super Mode transition expectation is routine behavior; shared Mac scan-row reveal is framework behavior. Add relevant routine coverage labels separately. Documentation-only changes need no device coverage. Use the canonical independent codex-pr-review skill and its existing launcher on every opened or updated PR. Read its verdict and all relevant requested changes; address real findings, explain evidence-backed disagreements, and rerun review after changing the head. Do not substitute self-review or a bare reviewer agent. See review and merge.

Merge only with an approving canonical review on the exact current head and passing required checks, under the task's merge authority. Reconcile uncertain push/PR/review/merge outcomes before retrying. Continue this lifecycle without asking for authorization already supplied by the task. Keep credentials, private logs and recordings out of public PRs/comments.

Show full SKILL.md (663 more words)Show less

Choose useful verification

Use the smallest verification that can distinguish the cause. Strong causal source evidence may need focused regression checks and ordinary targeted replay; source-only fixes do not need an authoring session. When device inspection or action iteration is genuinely necessary, reuse a compatible built-in routine-work create/edit job or submit one for a representative routine with the group's evidence and needed observation. Follow authoring operations.

Each job names one routine and target. Distinct unresolved device work or incompatible platform/source/build targeting can require separate jobs. The supervisor owns its workspace, agent, scoped connection, reservation and held session; raw author commands are inner job operations. Keep the proven prefix, safe prerequisite state and saved action. Finish and return through the job normally. An authoring section is not an ordinary passing run.

If verification needs merged source not yet installed, record the exact pending deployment prerequisite and its actual owner. Continue independent diagnoses, source fixes and PR work. Do not take over deployment or make a general coordinator handoff a stopping gate. Required merge checks still apply; distinguish optional deferred device evidence from a check that actually blocks merging. Prefer linked reruns for suite members once the endpoint is deployed: dispatch a fixed item immediately, or batch compatible ready items. Omit the app source to reuse each original artifact; supply an optional exact publication override only when testing an app fix. Framework fixes require the corrected installed source; verify its receipt rather than requesting a framework revision through this API. Read latest attempts first and adopt accepted equivalent work. Retain stable rerun IDs and preview digests across uncertain transport retries. For an unaccepted preview that has definitively expired, create a new ID and preview; accepted submissions always reconcile their existing identity. A deliberate next attempt gets a new ID and terminal predecessor. Never repeat passing long tests merely to verify a shared fix. See the linked API in operations. A new failure returns to diagnosis, not an automatic full-suite retry loop.

Continue efficiently through long waits

Keep a compact continuation record beside the ledger: phase, stable suite/job/PR identities, next action, prerequisite, owner, last receipt and resume trigger. When a prerequisite settles, perform the next authorized action in the same turn. “Ready,” idle lanes and queued handoffs are milestones, not completion.

Do useful source work during a long suite or review, then use a supported long poll or genuinely verified durable wakeup. Read the wait procedure. Consume changed-state projections; avoid repeatedly loading complete results, logs or transcripts. Report useful changes: new diagnosis, fixed cause, review finding, merged PR or a specific blocker and next action. Stay quiet while nothing changes. Never claim a queued message or notification-only timer will resume this chat. If no resume mechanism exists, report that execution gap and the saved continuation instead of claiming autonomous completion is arranged. Use available bounded waiting while preserving work; do not introduce a queue/timer framework.

Report merged fixes and honest limits

Finish when each observed failure has a targeted verification result for its approved merged fix or equivalent, an evidence-backed machine/fixture conclusion, or an explicitly unavailable deployment/access prerequisite with next action and owner. A source fix with available verification is not completion; dispatch it and consume its result. Do not hide an unresolved failure to claim completion. If members are still running, report the observed coverage and continue via the verified resume path to consume remaining results. Preserve concise receipts and evidence links; clean disposable owned worktrees through normal operations. Flag any removed system without an improved replacement for a follow-up spec. Do not delete native chat history or keep a parallel archive of run downloads.

Final report example:

Suite <stable link>: 28/28 members terminal; original verdict failed. Shared download cause: fixed in <merged PR>, approved at <head>; focused tests passed. Pairing: <conclusion and merged PR or unresolved dependency>. Device replay was not performed because <exact source> awaits deployment by <owner>. No new suite was started and no passing-suite claim is made. Remaining work: <specific item>.

© Mentra-Community, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in .agents/skills/fix-nightly-failures of Mentra-Community/MentraOS.

  • SKILL.md
  • agents/openai.yaml
  • references/operations.md

Open the folder on GitHubat commit bc626e0

Compare with similar skills

Fix Nightly Failures next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Fix Nightly Failures compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
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KubeSphere ServiceMesh Managerkubesphere/kubesphere17k—~2.4kAutomated safety check: PassCustom licence
Vercelremotion-dev/remotion63k—~1.2kAutomated safety check: PassCustom licence
AWS Cdk Developmentzxkane/aws-skills3672 repos~2.5kAutomated safety check: PassMIT

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Categories

Questions about Fix Nightly Failures

What does Fix Nightly Failures do?

Diagnose an ongoing or finished Mentra nightly suite, group demonstrated shared failures, implement fixes, and carry PRs through independent Codex review and merge. Fix Nightly Failures is an agent skill from Mentra-Community/MentraOS. Diagnose an ongoing or finished Mentra nightly suite, group demonstrated shared failures, implement fixes, and carry PRs through independent Codex review and merge.

When should I use Fix Nightly Failures?

Fix Nightly Failures fits situations like: A chat is pointed at a nightly suite; deployment and a new full suite are separate work.

How do I install Fix Nightly Failures in Claude Code?

Run `npx skills add Mentra-Community/MentraOS --skill fix-nightly-failures -a claude-code`. Or copy the skill folder (.agents/skills/fix-nightly-failures in Mentra-Community/MentraOS) into .claude/skills/fix-nightly-failures in your project. Claude Code loads it when a task matches its description.

How do I install Fix Nightly Failures in Codex?

Run `npx skills add Mentra-Community/MentraOS --skill fix-nightly-failures -a codex`. Or copy the skill folder (.agents/skills/fix-nightly-failures in Mentra-Community/MentraOS) into .agents/skills/fix-nightly-failures in your project. Codex loads it when a task matches its description.

Can I use Fix Nightly Failures in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Mentra-Community/MentraOS --skill fix-nightly-failures -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fix-nightly-failures, .gemini/skills/fix-nightly-failures, .github/skills/fix-nightly-failures and .opencode/skills/fix-nightly-failures in your project.

What does Fix Nightly Failures need to run?

SKILL.md names no scripts, command-line tools or credentials: Fix Nightly Failures is instructions for the agent only.

Does Fix Nightly Failures access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Fix Nightly Failures safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Fix Nightly Failures use?

Fix Nightly Failures is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fix Nightly Failures use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.8k tokens, read only when the agent opens those files.

What are the alternatives to Fix Nightly Failures?

Skills that share tags, products or a category with Fix Nightly Failures: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Vercel (remotion-dev/remotion, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fix Nightly Failures?

Mentra-Community (a GitHub organization) maintains it in Mentra-Community/MentraOS, which has 2,381 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 10, 2026.

Source: Mentra-Community/MentraOS on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.