Factually incorrect and suggested scripts and files not existent
まだ誰も着手していません。
- 主要言語
- Shell
- スター
- 11.2k
- フォーク
- 1.9k
- 平均マージ
- 14時間 16分
- マージ済み PR(30日)
- 6
説明
Describe the bug
The model described steps to perform the data discovery and alert building based upon the current files existing in the folder. However, although the steps sound logical and positively feasible, the files such as render.py, compare.py. etc are not truly present. They are purely made up by the model, in addition, when assessing the details about the crosswalk from index to the datastream in elastic, although the actual file was there in .csv format, the suggested transition from the index to the stream mentioned by the model was not existing in reality. The name of the dataset is not real either.
Affected version
No response
Steps to reproduce the behavior
Here is the step-by-step practical guide using the (redacted)/ as our working example.
────────────────────
End-to-End Workflow Map
[ Step 1: Data Discovery & Crosswalk ]
│ (Find source index, target datastream & ECS fields)
▼
[ Step 2: ES|QL Query Formulation & Data Evidence ]
│ (Convert SPL → ES|QL & test in Jupyter / Dev Tools)
▼
[ Step 3: YAML Specification & JSON Rendering ]
│ (Write spec-*.yaml → run render_alert.py)
▼
[ Step 4: Dry-Run Diff & Push to Kibana ]
│ (compare_alerts.py → render_alert.py --push)
▼
[ Step 5: Master Index Confirmation ]
(Update ALERTS_INDEX.md status)
────────────────────
Step 1: Data Discovery & Crosswalk Mapping
Goal: Determine where the Splunk data lives in Elasticsearch.
- Inspect the original Splunk query (from redacted):
index=redacted apiName="inf-bnkng-party-physaccsprof-accsprofvecos-v1"
| where apiPath="redacted"
| where responseCode >= 400 - Find the target Data Stream:
Look up in data/Kibana_dashboard_objects/...CROSSWALK.csv :
• Splunk redacted redacted logs $\rightarrow$ redacted
• Dataset: redacted - Map the Fields:
• apiPath $\rightarrow$ redacted
• redacted $\rightarrow$ redacted
────────────────────
Step 2: ES|QL Formulation & Data Evidence
Goal: Formulate and test the query against live data to verify hits.
- ES|QL Query Formulation:
redacted - Test & Verify:
• Run in Kibana Discover $\rightarrow$ ES|QL tab or in a verification notebook ( redacted.md ).
• Confirmation Criteria: Ensure no field type errors and that the count calculation matches expected failure counts.
────────────────────
Step 3: Create redacted
Goal: Avoid writing bulky Kibana JSON by using human-readable YAML.
- Create or edit the YAML spec ( redacted):
rule_id: "auto"
name: "redacted"
tags: ["redacted"]
schedule_interval: "5m"
time_window:
size: 5
unit: "m"
esql: |
redacted
email:
to: ["redacted]
subject: "{{context.hits.0._source.labels.environment}} - redacted."
snow:
node: "redacted"
resource: "/"
metric_name: "redacted"
short_description: "redacted" - Execute Python Rendering Script:
────────────────────
Step 4: Diff & Push to Kibana
### Expected behavior
Accurate to the individual details mentioned in the response from the file names, contents and inferred information (at least logical instead of making it up). The model should have suggested to create the files, instead of making them up to mislead.
### Additional context
_No response_
コントリビューションガイド
はじめの一歩
- issue を最後まで読み、次にプロジェクトのコントリビューションガイドを読みます。
- 着手することを issue にコメントします — 二人が同じ作業をするのを防げます。
- リポジトリをフォークし、ブランチを切って変更します。
- issue 番号を参照したプルリクエストを送ります。
調査の方向性
まず copilot-cli で報告されたワークフローを再現し、生成された参照を data/Kibana_dashboard_objects/...CROSSWALK.csv および利用可能な検証 notebook と比較します。モデルが render.py、compare.py、render_alert.py、compare_alerts.py、および dataset 名をどのように提示するかを確認します。生成されたガイダンスが既存のファイルとデータを提案されたファイルと区別するか、作成手順を明確に示していれば完了です。
索引モデルが issue の本文から書いたものです。
評価
- 技術スタック
- elasticsearch, python, shell, yaml
- 領域
- ai, cli
- issue の種類
- バグ
- 難易度
- 5/5
- 見積もり時間
- 1週間以上
- 活発さ
- 活発
- 明瞭さ
- 説明が足りない
- 初心者へのやさしさ
- 25/100