Projete e verifique a saída de runtime observável para scripts em Python, PowerShell ou Node.js que realizam operações em massa ou requisições de API.
- Estrelas no GitHub
- 41.038
- Arquivos
- 6
- Último commit
- 11 de nov. de 2026
- Licença
- MIT
- Ferramentas permitidas
- —
O que a skill batch-script-progress faz?
batch-script-progress é uma Agent Skill. Projete e verifique a saída de runtime observável para scripts em Python, PowerShell ou Node.js que realizam operações em massa ou requisições de API.
Resumo gerado a partir do SKILL.md da skill.
Sobre a skill batch-script-progress
Desenvolvedores que criam scripts em Python, PowerShell ou Node.js para operações em massa podem usar esta SKILL para projetar e verificar a saída de runtime observável. O foco é criar um contrato estruturado para o reporte de progresso, falhas de itens e resumos finais sem alterar a lógica de processamento subjacente ou o status de saída do script. Isso é particularmente útil para loops de longa duração, lotes de requisições de API ou tarefas de processamento de arquivos onde a execução silenciosa dificulta o monitoramento.
Um agente deve carregar esta skill quando precisar modificar um script para incluir notificações de início, atualizações periódicas de progresso e resumos de terminal. A skill garante que os dados de progresso sejam enviados para um canal separado, como o stderr, para evitar a poluição do stream de resultados principal no stdout. Ela se baseia em padrões de implementação específicos para diferentes runtimes e inclui um verificador multiplataforma para provar que a saída é visível enquanto o processo ainda está rodando. Os usuários devem observar que isso não se destina a barras de progresso de UI ou infraestrutura de monitoramento, mas para estabelecer streams de diagnóstico confiáveis, legíveis por máquina ou por humanos.
O que um agente pode fazer com ela
- 1Adicionar progresso a scripts de API em massaModificar um script Node.js que realiza muitas requisições de API para reportar contagens de itens processados, bem-sucedidos e falhas via stderr.
- 2Garantir a consistência do status de saídaAtualizar um script de lote Python para incluir um resumo dos resultados, preservando seu contrato original de exit code.
- 3Implementar reporte de erros seguroConfigurar um script para emitir motivos de falha sanitizados para itens individuais sem despejar exceções brutas ou dados sensíveis.
Escrito a partir do SKILL.md da skill. Cada caso de uso é verificado com uma citação dele.
Como instalar a skill batch-script-progress
Cada comando copia a pasta da skill para o diretório de skills do cliente. Reinicie o cliente ou inicie uma nova sessão para carregá-la.Instalar a skill batch-script-progress no Claude Code
~/.claude/skills/batch-script-progress/SKILL.md
$ npx degit github/awesome-copilot/skills/batch-script-progress ~/.claude/skills/batch-script-progressInstalar a skill batch-script-progress no Claude Code (project)
.claude/skills/batch-script-progress/SKILL.md
$ npx degit github/awesome-copilot/skills/batch-script-progress .claude/skills/batch-script-progressInstalar a skill batch-script-progress no Codex
~/.agents/skills/batch-script-progress/SKILL.md
$ npx degit github/awesome-copilot/skills/batch-script-progress ~/.agents/skills/batch-script-progressInstalar a skill batch-script-progress no Gemini CLI
~/.gemini/skills/batch-script-progress/SKILL.md
$ npx degit github/awesome-copilot/skills/batch-script-progress ~/.gemini/skills/batch-script-progressInstalar a skill batch-script-progress no Claude.ai
npx degit github/awesome-copilot/skills/batch-script-progress batch-script-progress && zip -r batch-script-progress.zip batch-script-progress # claude.ai → Customize → Skills → + → Create skill → Upload a skill → batch-script-progress.zip
Verificações automatizadas
Executado em 13 de nov. de 2026Relatório completo →Passou nas nossas verificações automáticas. Não é uma auditoria de segurança: leia os scripts antes de deixar um agente executá-los. Como as verificações funcionam
- Repositório de origem vinculado e acessívelgithub/awesome-copilot/skills/batch-script-progress is public and reachablegithub.com/github/awesome-copilot/tree/HEAD/skills/batch-scr ↗Passou
- Licença de código aberto (OSI)MITspdx.org/licenses/MIT.html ↗Passou
- Commit ou release no último anoLast commit 2026-11-11github.com/github/awesome-copilot/commits ↗Passou
- Sem baixar e executar nem roubo de credenciais nos scripts3 scripts read; no download-and-run, remote eval, base64 execution or credential uploadPassou
- Sem instruções ocultas no SKILL.mdNo override phrases, safeguard switches, credential requests or hidden charactersgithub.com/github/awesome-copilot/blob/HEAD/skills/batch-scr ↗Passou
- Ferramentas pré-aprovadas são restritasNo pre-approved tools; the agent asks before using onegithub.com/github/awesome-copilot/blob/HEAD/skills/batch-scr ↗Passou
SKILL.md
Ver no GitHubBatch Script Progress
Make generated batch scripts observable while they run, without changing their processing contract. Design start, periodic progress, per-item failure, and final-summary output together with result streams and exit status. A progress-bar library alone does not establish this contract.
1. Fix the existing contract
Read the script, callers, and nearby tests before editing. Identify:
- Input unit, known or unknown total, and whether enumeration is lazy.
- Existing stdout format and consumers, runtime version, and interactive versus redirected execution.
- Continue-on-error or fail-fast policy, retry rules, skip rules, transaction boundaries, and cancellation behavior.
- Existing exit codes and what callers treat as success.
Preserve these decisions. Do not add retries, parallelism, dependencies, or a new failure policy just to add progress output. If partial failures currently return zero, report the partial outcome honestly while keeping that exit contract. If the contract is missing or contradictory, ask for the decision that changes behavior; do not silently make it.
2. Define the output contract before implementation
Choose a small, stable vocabulary and fields, reusing the repository logger where suitable:
- Start: operation name, total or explicit unknown, and initial counters. Emit before expensive enumeration; discovery itself may need progress.
- Progress: processed, succeeded, failed, skipped, total or unknown, and elapsed time. Add a sanitized current-item identifier only when useful.
- Item failure: safe identifier, failure category or sanitized reason, and whether processing will continue. Emit when observed, independently of the normal progress interval.
- Summary: completed, partial, failed, or cancelled; final counters; elapsed time; known unprocessed count if available; and the exit status required by the existing contract.
Define processed = succeeded + failed + skipped for items that reached a terminal outcome. Keep in-flight and not-started items separate. Count each item once; retry attempts are not additional processed items. Do not label an item successful before its required commit, write, or acknowledgement. If a transaction rolls back, report rolled-back work rather than claiming durable success.
For an unknown total, report counts without a fabricated percentage, ETA, or remaining count. Do not materialize a stream just to count it. For zero items, emit start and summary with zero counts; never divide by zero.
3. Choose output streams and cadence
Reserve stdout for the established machine-readable result, pipeline objects, or protocol. Put progress and diagnostics on a separate channel; stderr is the portable default for standalone CLI scripts. Stderr output alone does not imply failure: callers must use the agreed exit code and result contract. Verify callers that treat any stderr as failure before changing their output. If stdout is reserved and stderr is incompatible, use an existing compatible logger or sink only when the caller already supports it. Do not move progress to stdout or another stream with changed semantics. If no compatible channel exists, stop and ask whether the output contract may change, or report that progress cannot be added safely.
Use a bounded cadence, such as every configured number of items or elapsed interval, rather than unconditionally logging every item. Emit start, failures, and summary regardless of that cadence. Preserve required per-item audit records separately. Avoid unbounded in-memory failure lists and repeated stack traces. Redact credentials, query parameters, personal data, and sensitive paths before formatting; do not dump raw exceptions or whole input records by default.
Use monotonic time for intervals and duration. Ensure output is flushed or drained so notifications arrive before exit. Use plain newline-delimited records under redirection; enable terminal rewriting or colors only for an appropriate TTY. Keep log-field meanings consistent across languages, not necessarily their exact formatting or libraries.
A time check at the end of a loop cannot emit while one item is blocking. For a long item, use existing progress callbacks, stage notifications, or a safely integrated heartbeat where the runtime permits it. A Node.js timer cannot run through synchronous event-loop blocking; a PowerShell progress display is not a durable log. If mid-item progress cannot be added without changing execution semantics, emit the current stage before it starts and disclose the notification gap. Do not promise a periodic heartbeat that the implementation cannot deliver.
4. Implement the smallest compatible change
Read language notes and safe examples for the selected runtime. The examples are executable output-contract probes, not production processors; adapt their emitter and accounting to the existing code rather than copying their failure policy.
Keep reporting separate from processing decisions. In concurrent code, serialize reporting through the coordinator and count completed outcomes, not submissions. On handled failure or cancellation, attempt one final summary and preserve the original outcome; a summary-write error must not replace the original processing exception. Do not swallow cancellation as an ordinary item failure. For host-managed cancellation, including PowerShell host stops, preserve the existing host behavior; do not convert stop exceptions into item failures or promise a final summary after host termination. Use finally for applicable cleanup, but verify the actual cancellation path in the supported host when graceful cancellation is part of the contract.
Do not force successful termination to deliver buffered output. In Node.js prefer setting process.exitCode and draining writes over an immediate process.exit(). Respect existing host/library semantics in PowerShell: a reusable function should not exit its caller. Forced termination, process crashes, and broken output pipes can prevent final reporting; do not claim otherwise.
5. Verify before reporting completion
Read verification cases, then run focused tests for the changed script with harmless fixtures. Capture stdout and stderr separately and check the real exit status. Verify start/progress ordering, monotonic counters, sanitized failures, exactly one summary on supported paths, and unchanged result contents and processing policy.
Prove liveness by reading the child process output while it is still running, not by examining output collected after exit. Check both terminal and redirected behavior when both are supported. A controlled pause after a progress event is a useful deterministic probe: receive the event, confirm the child has not exited, then release it. Keep such gates in harmless test fixtures or the test harness; do not add stdin waits, sleeps, or cancellation hooks to normal production processing solely to make a test pass. Prefer an existing callback or injectable processing boundary. If no safe deterministic seam exists, test the real path only with harmless inputs or report liveness as unverified. A watchdog may fail the test; it must not manufacture a successful result.
The bundled cross-language verifier runs the Python, PowerShell, and Node.js probes with normal, partial-failure, preserved partial-failure exit-zero, empty, unknown-total, fail-fast, simulated-cancellation, and live-output cases. It checks the probes only; it does not prove that an arbitrary generated script or automatic skill selection works.
Run it from this skill folder with Node.js 20 or later:
node tests/verify-examples.mjs
It also requires Python 3.9 or later and PowerShell 5.1 or later. See the language notes for executable overrides. Missing runtimes are failures, not silently skipped coverage.
Deliverables
Return the changed script, its output/exit contract, and focused verification results. Distinguish executed tests from inspection and unexecuted cases. Do not call the script verified merely because it prints a progress bar or the skill metadata passes validation.
Gotchas
- Counting before logging can make discovery silently consume an entire stream.
- Writing status with PowerShell
Write-Outputadds strings to the success pipeline. - Measuring only buffered output after exit cannot prove progress visibility.
- A final message saying
completedhides partial failure unless the outcome and counters explain it. finallyis not a guarantee of reporting after forced termination.
Arquivos desta skill
6Perguntas sobre a skill batch-script-progress
Como instalo a skill batch-script-progress no Claude Code?
Execute npx degit github/awesome-copilot/skills/batch-script-progress ~/.claude/skills/batch-script-progress. O Claude Code carrega skills de ~/.claude/skills (todos os projetos) ou .claude/skills (um projeto) e usa uma skill quando a descrição dela corresponde à tarefa.
Quais clientes podem usar a skill batch-script-progress?
Qualquer cliente que leia o formato Agent Skills: Claude Code, Codex, Gemini CLI e claude.ai (envie como ZIP). Scripts da skill são executados apenas onde o cliente permite execução de código.
Como o progresso deve ser reportado se o número total de itens for desconhecido?
Reporte as contagens sem usar porcentagens fabricadas, ETAs ou contagens restantes. Não materialize um stream apenas para contá-lo.
Para onde as informações de progresso e diagnóstico devem ser enviadas em um script CLI?
O progresso e os diagnósticos devem ser colocados em um canal separado, sendo o stderr o padrão portátil para scripts standalone, enquanto o stdout deve ser reservado para resultados legíveis por máquina.
Como garantir que o progresso seja realmente visível durante a execução?
Você deve provar a vivacidade (liveness) lendo a saída do processo filho enquanto ele ainda está em execução, em vez de examinar a saída coletada após o encerramento do processo.