본문으로 건너뛰기
cccskills
무료GitHub에 공개

file-issue

Turn a bug report, improvement request, or experiment into a structured GitHub issue. Check for duplicates, write reproduction steps or testable completion criteria, apply suitable labels, and verify the published title and body.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

File a GitHub issue only when explicitly requested or delegated by another selected workflow; do not create issues merely because a problem was found.

연동 도구GitHub
설치 방법 보기

이럴 때 유용합니다

  • File a bug with clear reproduction steps
  • Create an improvement task with testable completion criteria
  • Track an experiment's hypothesis, status, and conclusions
  • Check for existing issues before filing new work

포함된 파일(1)

  • SKILL.md4.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

File a GitHub issue

Before drafting, read AGENTS.md and:

  • .agents/skills/writing-style/SKILL.md
  • .agents/skills/writing-style/issues.md
  • .agents/skills/writing-style/ai-writing-donts.md

Issue Kinds and Body Structure

Pick the smallest matching structure.

KindWhen to useLabels
bugA bug or regression was foundbug, agent-generated
taskAn improvement, refactor, or feature requestagent-generated + priority if known
experimentAn experiment needs trackingexperiment, agent-generated

Bug body

<what is broken and its impact -- concrete symptoms or error messages>

Reproduce:
1. <step>
2. <step>

Expected: <what should happen instead>

<optional: concise evidence or confirmed root cause>

Task body

<what needs to be done and why -- enough context for anyone on the team>

Done when:
<specific, testable completion criteria>

Experiment body

## TL;DR

<One-paragraph current summary. Leave blank only when the work is just being kicked off.>

## Description

<Context someone outside the thread can understand.>

## Hypothesis or Goal

<What are you trying to learn, fix, or achieve?>

## Status

<Current state; update as evidence lands.>

## Links

* Logbook:
* W&B Report:
* Important updates:

## Decision Log

## Conclusion

Workflow

1. Gather and classify

Extract the symptom or desired outcome, impact, location, reproduction, known cause, and severity. Ask when the issue or its kind is ambiguous.

2. Check duplicates

Search for existing issues first:

gh issue list --repo marin-community/marin --state open --search "<keyword>"

If a match exists, tell the user and offer to comment on it instead.

3. Draft

Title: At most 80 characters, optionally prefixed with a scope tag. State a factual symptom for a bug (e.g. [levanter] Gradient accumulation drops the last microbatch) and an imperative outcome for a task (e.g. [levanter] Handle partial accumulation steps). Do not add bug:, task:, or another type prefix.

Use the body structure above. Keep the facts needed to act; link code with file:line, trim errors to relevant frames, and omit filler, repeated titles, diff inventories, and unnecessary implementation narration. Bugs need numbered reproduction steps; tasks need testable completion criteria.

4. Inspect the payload

Apply the writing-style final compression pass to the exact title and body that will be sent to GitHub. For a bug or task, verify the title is at most 80 characters. Every remaining sentence must add a symptom, impact, reproduction step, observation, expected behavior, or completion criterion.

5. Apply the approval boundary

If the user explicitly asked to file an issue, skip the preview — file it and share the link. If the agent surfaced the issue (not explicitly requested), show the drafted title and body and wait for approval or edits.

6. File the issue

Write the body to a uniquely named temp file, then pass it with --body-file. Do not inline the body with shell substitution (--body "$(cat <<'EOF' ...)") — multiline text can be corrupted by pasted output or escaping mistakes. Do not reuse a fixed path like /tmp/issue-body.md; concurrent agent runs can overwrite each other's drafts on shared hosts.

body_file="$(mktemp "${TMPDIR:-/tmp}/issue-body.XXXXXX.md")"
trap 'rm -f "$body_file"' EXIT

cat > "$body_file" <<'EOF'
<body>
EOF

issue_url="$(gh issue create --repo marin-community/marin \
  --title "<title>" \
  --label "agent-generated" \
  --body-file "$body_file")"

Add kind-appropriate labels (bug, experiment). If a relevant label does not exist, skip it rather than creating new labels. For task issues, add a priority label (p1, p2, p3) if the user specifies one or severity is clear.

Before creating the issue, re-open the body file and verify it contains no unrelated shell output (pre-commit logs, pytest session headers, prompt transcripts). If it does, clean the draft before posting.

After creating the issue, fetch its published text with gh issue view "$issue_url" --json title,body and correct any text added or altered by the publishing tool.

7. Report

Print the issue URL.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Compare Zephyr changes using the same prepared dataset and matching execution settings. Analyze Finelog metrics for each processing stage to distinguish CPU efficiency, elapsed time, and peak memory changes, then report improvements, regressions, or tradeoffs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Compare Zephyr performance before and after a PR
  • Assess speed gains against additional CPU usage
  • Check peak memory and out-of-memory regressions
marin-community/marin4천2026년 10월 21일 업데이트

Register Hugging Face datasets for Marin by inspecting their structure without downloading the full dataset. Identify text fields, configurations, and data splits, then add a dataset module and validate the mapping with a sample.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Registering a Hugging Face dataset for Marin
  • Inspecting text fields without a full dataset download
  • Checking configurations and data splits
marin-community/marin4천2026년 10월 21일 업데이트

add-grant

무료

Turn a specified GCP access request into a reviewable Pulumi change and pull request. Select the narrowest suitable role and encrypt personal email identities, covering resource permissions and Cloud Run viewer access through IAP, an access gateway.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Prepare a request for GCS bucket read access
  • Add a viewer to a Cloud Run service protected by IAP
  • Prepare service account impersonation permissions
marin-community/marin4천2026년 10월 21일 업데이트

Add or update Pallas/Mosaic kernels, specialized computation routines for JAX. The skill covers reference implementations, output and gradient checks, public wrappers, fallback behavior, performance benchmarks, and hardware-specific tuning when requested.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Adding a Pallas kernel for a JAX computation
  • Checking outputs and gradients against a reference
  • Maintaining backend selection and fallback behavior
marin-community/marin4천2026년 10월 21일 업데이트

Preserve old experiment scripts with a dated Git tag, a named snapshot of the code, and add comments linking related GitHub issues to the archived files and cleanup pull request.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Preserving a snapshot of old experiment scripts
  • Linking experiment issues to archived files
  • Updating archive notices after a tag changes
marin-community/marin4천2026년 10월 21일 업데이트

Launch and continuously monitor a specified Zephyr pipeline on Iris when asked. It checks coordinator and worker health, tracks stage progress, identifies stalled or repeated failures, and requires explicit approval before stopping or restarting jobs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Launch a specified Zephyr pipeline and check startup
  • Monitor stage progress and worker health over time
  • Investigate stalled stages or repeated worker failures
marin-community/marin4천2026년 10월 21일 업데이트

marin-community의 스킬 모두 보기

이 스킬의 문제 신고