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ai-issue-report

Reports a reproducible fault to a team or an upstream project — for ai-engineering itself or for any service the client is building — as a governed payload: clo

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Harga belum dikonfirmasi★ 55 Star GitHubDirektori diperbarui · 9 Okt 2026agent-skill

Ringkasan

Reports a reproducible fault to a team or an upstream project — for ai-engineering itself or for any service the client is building — as a governed payload: closed allow-listed fields, scanned for machine paths, personal data (PII) and secrets before anything is written, draft kept local, and the exact bytes shown with their SHA-256 before anybody confirms anything. Trigger for "report this bug", "file an issue", "the framework is broken", "send this upstream", "write the incident report". Not for a fault in your own code that still needs a diagnosis — use /ai-debug first. Not for a vulnerability sent anywhere public: that routes to private disclosure, and this skill refuses the other way.

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Dokumentasi sumber, bukan instruksi untuk situs ini. Periksa izin sebelum menjalankan perintah.

ai-issue-report — report the fault, collect nothing on the way

What it produces

A local draft (gitignored) plus the exact bytes that would leave, previewed with their SHA-256 — and nothing sent by anybody but the user.

The non-negotiable: what must never leave the machine

The payload is closed to allow-listed fields. Everything else is rejected at the gate, before the draft exists:

Machine paths — home directories and absolute paths on any OS: they leak the username and the project layout. The scan names the field and the match (ACCEPTANCE_MACHINE_PATH_*); the fix is to describe the same thing without the path.
Personal data (PII) — emails, names, phone numbers, account ids, tokens in URLs. ACCEPTANCE_PII_* names what was found; rewrite the sentence, not around the value.
Secrets — keys, passwords, session cookies, anything gitleaks would flag. ACCEPTANCE_GITLEAKS_SECRET is a hard refusal: no draft is written at all.
Logs, diffs, tracebacks, full command lines — there is no field for them, by design. A pasted command carries the path it ran from and often the arguments it ran with. Write the four fields in your own words instead: title, what happened, what you expected, one step per reproduction step.

A vulnerability (--kind security) NEVER becomes a public issue: the refusal prints the private disclosure route (SECURITY.md, the maintainer's security contact) and declines the public one before asking anything.

Steps

Reproduce it first. A report of something that happened once is a report the person reading it cannot act on; the steps field is what makes the difference.
Decide the kind before writing. Security → private route, always.
Write the four fields in your own words. Never paste logs, diffs or tracebacks.
Run the gate. Read the refusal if you get one: each code names what was found and in which field. Rewrite that field in words that do not carry the value — do not work around the scan.
Read the previewed bytes and their SHA-256. They are exactly what would leave. If anything in there is not yours to publish, stop.
Sending is separate and manual. Nothing is transmitted automatically: take the previewed bytes to the route your organisation or the upstream project uses (GitHub issue for bugs, SECURITY.md contact for vulnerabilities, your incident channel for incidents).

Writing the prose

The write-up follows the framework's single writing standard — read it before writing the fields: ai-write › references/documentation-writer.md. One idea per sentence, one meaning per word, nothing the environment already says. When the report is long (an incident post-mortem rather than a bug), hand the prose to /ai-write and keep this skill's gate as the last step before publishing.

The ai-engineering seam

The governed post-mortem lives at .ai-engineering/reports/NNN-{slug}.html — readable without session context; the NNN numbering is never rewritten.
It is immune while DECISIONS.md cites it; uncited, it expires to gc (§21.3) — history is not rewritten, it is archived in git.
The gate (paths/PII/secrets) runs on ANY text destined to leave a governed repo — it is the same discipline the git floor's gitleaks stage enforces at commit time, applied one step earlier, to prose.

Routing

In scope: reproducible faults bound for a team, an upstream project, or an incident review. Not for: undiagnosed faults (/ai-debug), internal findings worth remembering (/ai-note), decisions (/ai-plan), the docs themselves (/ai-write).

Lifecycle

Lane: any Writes: .ai-engineering/reports/NNN-{slug}.html Read by: the team, humans without session context Dies: immune while a permanent governor cites it; doctor --gc after older_than when nothing cites it Next: none

Source: ai-engineering v1 skill ai-report (own), Apache-2.0 — renamed ai-issue-report.

Lihat sumber ↗

Metadata berkas

name: ai-issue-report
description: >-
  Reports a reproducible fault to a team or an upstream project — for ai-engineering itself
  or for any service the client is building — as a governed payload: closed allow-listed
  fields, scanned for machine paths, personal data (PII) and secrets before anything is
  written, draft kept local, and the exact bytes shown with their SHA-256 before anybody
  confirms anything. Trigger for "report this bug", "file an issue", "the framework is
  broken", "send this upstream", "write the incident report". Not for a fault in your own
  code that still needs a diagnosis — use /ai-debug first. Not for a vulnerability sent
  anywhere public: that routes to private disclosure, and this skill refuses the other way.
license: Apache-2.0

Lihat teks asli

---
name: ai-issue-report
description: >-
  Reports a reproducible fault to a team or an upstream project — for ai-engineering itself
  or for any service the client is building — as a governed payload: closed allow-listed
  fields, scanned for machine paths, personal data (PII) and secrets before anything is
  written, draft kept local, and the exact bytes shown with their SHA-256 before anybody
  confirms anything. Trigger for "report this bug", "file an issue", "the framework is
  broken", "send this upstream", "write the incident report". Not for a fault in your own
  code that still needs a diagnosis — use /ai-debug first. Not for a vulnerability sent
  anywhere public: that routes to private disclosure, and this skill refuses the other way.
license: Apache-2.0
---

# ai-issue-report — report the fault, collect nothing on the way

## What it produces

A local draft (gitignored) plus the exact bytes that would leave, previewed with their
SHA-256 — and nothing sent by anybody but the user.

## The non-negotiable: what must never leave the machine

The payload is closed to allow-listed fields. Everything else is rejected at the gate,
before the draft exists:

- **Machine paths** — home directories and absolute paths on any OS: they leak the
  username and the project layout. The scan names the field and the match
  (`ACCEPTANCE_MACHINE_PATH_*`); the fix is to describe the same thing without the path.
- **Personal data (PII)** — emails, names, phone numbers, account ids, tokens in URLs.
  `ACCEPTANCE_PII_*` names what was found; rewrite the sentence, not around the value.
- **Secrets** — keys, passwords, session cookies, anything gitleaks would flag.
  `ACCEPTANCE_GITLEAKS_SECRET` is a hard refusal: no draft is written at all.
- **Logs, diffs, tracebacks, full command lines** — there is no field for them, by design.
  A pasted command carries the path it ran from and often the arguments it ran with. Write
  the four fields in your own words instead: title, what happened, what you expected, one
  step per reproduction step.

A vulnerability (`--kind security`) NEVER becomes a public issue: the refusal prints the
private disclosure route (SECURITY.md, the maintainer's security contact) and declines the
public one before asking anything.

## Steps

1. Reproduce it first. A report of something that happened once is a report the person
   reading it cannot act on; the steps field is what makes the difference.
2. Decide the kind before writing. Security → private route, always.
3. Write the four fields in your own words. Never paste logs, diffs or tracebacks.
4. Run the gate. Read the refusal if you get one: each code names what was found and in
   which field. Rewrite that field in words that do not carry the value — do not work
   around the scan.
5. Read the previewed bytes and their SHA-256. They are exactly what would leave. If
   anything in there is not yours to publish, stop.
6. Sending is separate and manual. Nothing is transmitted automatically: take the previewed
   bytes to the route your organisation or the upstream project uses (GitHub issue for
   bugs, SECURITY.md contact for vulnerabilities, your incident channel for incidents).

## Writing the prose

The write-up follows the framework's single writing standard — read it before writing the
fields: [ai-write › references/documentation-writer.md](../ai-write/references/documentation-writer.md).
One idea per sentence, one meaning per word, nothing the environment already says. When the
report is long (an incident post-mortem rather than a bug), hand the prose to /ai-write and
keep this skill's gate as the last step before publishing.

## The ai-engineering seam

1. The governed post-mortem lives at `.ai-engineering/reports/NNN-{slug}.html` — readable
   without session context; the NNN numbering is never rewritten.
2. It is immune while DECISIONS.md cites it; uncited, it expires to gc (§21.3) — history is
   not rewritten, it is archived in git.
3. The gate (paths/PII/secrets) runs on ANY text destined to leave a governed repo — it is
   the same discipline the git floor's gitleaks stage enforces at commit time, applied one
   step earlier, to prose.

## Routing

In scope: reproducible faults bound for a team, an upstream project, or an incident review.
Not for: undiagnosed faults (/ai-debug), internal findings worth remembering (/ai-note),
decisions (/ai-plan), the docs themselves (/ai-write).

## Lifecycle

Lane: any
Writes: .ai-engineering/reports/NNN-{slug}.html
Read by: the team, humans without session context
Dies: immune while a permanent governor cites it; doctor --gc after older_than when nothing cites it
Next: none

Source: ai-engineering v1 skill `ai-report` (own), Apache-2.0 — renamed ai-issue-report.

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Harga dan biaya penggunaan

Dapatkan skill: Harga belum dikonfirmasi
Jalankan: Persyaratan belum dikonfirmasi. Periksa biaya agen, API, dan layanan di sumbernya.
Lisensi: Apache-2.0
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Sumber skill tercatat

Jalur instruksi telah dicatat. Ini bukan uji eksekusi, jaminan keamanan, atau sertifikasi kompatibilitas.

Tinjau sebelum memasang: Hindari pemasangan otomatis

Lisensi: Apache-2.0

Permission surface may require sandboxing
Persetujuan tinjauan AI belum ada
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 55 GitHub stars
Stars/forks activity: 55 stars, 3 forks; issue activity unavailable in current metadata
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Buka audit lengkap

Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.

Mulai dengan tugas kecil

1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.

Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.

Sumber dan catatan penggunaan

TerindeksDiperiksa statis

Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.

Repositori sumber: arcasilesgroup/ai-engineering
Lisensi: Apache-2.0
Versi: Unknown
Push GitHub terakhir: 16 Sep 2026
Direktori diperbarui: 9 Okt 2026
Jalur instruksi: skills/ai-issue-report/SKILL.md @ f7ea1cfd3d10

Versi dilaporkan dalam metadata direktori; periksa rilis sumber.

Kualitas

59/100

Menjanjikan

Kepercayaan

63/100

Hanya sandbox

Audit

75/100

Perlu ditinjau

Buka audit lengkap Lihat laporan evaluasi

Permission surface may require sandboxing
Persetujuan tinjauan AI belum ada
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 55 GitHub stars
Stars/forks activity: 55 stars, 3 forks; issue activity unavailable in current metadata
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Verified installs: —
Hasil: —

Menyalin bukan memasang. Jumlah instalasi memerlukan laporan berhasil dan bukan jaminan kualitas menyeluruh.

Akses agent

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka API pemasangan Format teks LLM Buka Manifest Rencana resolusi otomatis

Detail lainnya

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      "GitHub adoption: 55 GitHub stars",
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      "Permission surface: secrets or environment access, shell or command execution",
      "Review status: AI review approval is missing"
    ]
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      "Review status: AI review approval is missing"
    ]
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    "auto_install_policy": "block",
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    "human_review_required": true,
    "blocked": true,
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  "quality": {
    "score": 59,
    "label": "Promising"
  },
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    "maintenance": "27d since push",
    "risk": "Needs review"
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      "Audit: 75/100 Needs review",
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      "install_command": "npx skills add arcasilesgroup/ai-engineering --skill ai-issue-report",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "arcasilesgroup-ai-issue-report",
      "task": "Use ai-issue-report in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/arcasilesgroup-ai-issue-report",
    "api": "https://www.openagentskill.com/api/agent/skills/arcasilesgroup-ai-issue-report",
    "audit": "https://www.openagentskill.com/skills/arcasilesgroup-ai-issue-report/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=arcasilesgroup-ai-issue-report&task=Use%20ai-issue-report%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-issue-report%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20ai-issue-report%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/arcasilesgroup-ai-issue-report/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/arcasilesgroup-ai-issue-report"
  }
}

Untuk kreator

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator: arcasilesgroup
Sumber: arcasilesgroup/ai-engineering
Diindeks oleh: Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan arcasilesgroup, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit berbagi

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/arcasilesgroup-ai-issue-report?metric=listed&label=Listed)](https://www.openagentskill.com/skills/arcasilesgroup-ai-issue-report?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/arcasilesgroup-ai-issue-report?metric=trust&label=Trust)](https://www.openagentskill.com/skills/arcasilesgroup-ai-issue-report?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/arcasilesgroup-ai-issue-report?metric=audit&label=Audit)](https://www.openagentskill.com/skills/arcasilesgroup-ai-issue-report/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/arcasilesgroup-ai-issue-report?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/arcasilesgroup-ai-issue-report?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

Pratinjau badge Buka audit Kit kreator

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.