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asc-analytics-reports
Collect, download, and verify App Store Connect Analytics reports with asc. Use when users need to discover analytics report requests, select report instances by processing date or granularity, download every segment, or verify downloaded files against Apple's size and MD5 metada
概览
Collect, download, and verify App Store Connect Analytics reports with asc. Use when users need to discover analytics report requests, select report instances by processing date or granularity, download every segment, or verify downloaded files against Apple's size and MD5 metadata before analysis.
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asc analytics reports
Collect a complete set of analytics report segments and verify the compressed files before handing them to a separate analysis workflow. Do not interpret, aggregate, or present the report contents as part of this skill.
Guardrails
- Treat report inventories, signed URLs, downloaded segments, and identifiers as confidential business data.
- Prefer an existing request. Creating a request changes App Store Connect state
and requires an Admin-authorized profile; obtain explicit user approval before
running
asc analytics request. - Never delete or replace a request as part of collection.
- Use
asc analytics download; do not fetch or persist signed segment URLs separately. - Store private files outside the source repository with owner-only permissions.
- Do not claim the collection is complete if any expected segment is missing or fails verification.
1. Verify the CLI contract
Inspect the installed command before authentication or collection:
asc analytics view --help
Continue only when help lists --processing-date, --granularity,
--paginate, and --include-segments. These filters require asc 3.5.0 or
newer. If either filter is absent, ask the user to upgrade. Do not substitute
the deprecated --date flag because it uses legacy local matching rather than
Apple's server-side processing-date filter.
2. Prepare private storage
Create a private temporary directory outside the repository before capturing JSON or downloading segments:
umask 077
ASC_ANALYTICS_DIR="$(mktemp -d "${TMPDIR:-/tmp}/asc-analytics.XXXXXX")"
mkdir -m 700 "$ASC_ANALYTICS_DIR/segments"
Redirect command output and errors into this directory. Do not paste raw inventory JSON or error output into chat, commits, issues, or pull requests.
3. Find an existing request
Resolve the app ID and selected asc profile, then list every request:
asc --profile "$PROFILE" analytics requests \
--app "$APP_ID" \
--paginate \
--output json \
> "$ASC_ANALYTICS_DIR/requests.json" \
2> "$ASC_ANALYTICS_DIR/requests.stderr"
Inspect the JSON structurally and select an existing usable request. Do not rely
on --state when discovery works without it. If no usable request exists, stop
and ask whether the user wants to create ONGOING or ONE_TIME_SNAPSHOT
access. State the target app and profile before requesting approval. After
approval, prefer --reuse-existing to avoid duplicates:
asc --profile "$APPROVED_PROFILE" analytics request \
--app "$APP_ID" \
--access-type "$ACCESS_TYPE" \
--reuse-existing \
--output json \
> "$ASC_ANALYTICS_DIR/request.json" \
2> "$ASC_ANALYTICS_DIR/request.stderr"
Do not run that command without explicit approval. Read the returned request ID from the private JSON response before continuing:
REQUEST_ID="$(jq -er '.requestId' "$ASC_ANALYTICS_DIR/request.json")"
When a request was created or reused with the approved profile, set
ANALYTICS_PROFILE="$APPROVED_PROFILE". For an existing request discovered
with the read-only profile, set ANALYTICS_PROFILE="$PROFILE". Use that same
profile for every subsequent analytics view and analytics download call.
4. Discover and select report instances
First retrieve report and instance metadata without segment URLs:
asc --profile "$ANALYTICS_PROFILE" analytics view \
--request-id "$REQUEST_ID" \
--paginate \
--output json \
> "$ASC_ANALYTICS_DIR/discovery.json" \
2> "$ASC_ANALYTICS_DIR/discovery.stderr"
Select an available processingDate and the granularity requested by the user.
Accept DAILY, WEEKLY, and MONTHLY, individually or as a comma-separated
list. Split the input on commas, trim each token, and normalize it to uppercase.
Validate every token against that allowlist, including empty tokens. Report the
invalid input and stop before running analytics view; never silently discard
unsupported values or continue with an empty filter. After validation, remove
duplicates and join the remaining values with commas.
Treat processingDate as the date Apple processed the report, not necessarily
the period represented by its rows.
Retrieve the filtered inventory, including all segment metadata:
asc --profile "$ANALYTICS_PROFILE" analytics view \
--request-id "$REQUEST_ID" \
--processing-date "$PROCESSING_DATE" \
--granularity "$GRANULARITY" \
--paginate \
--include-segments \
--output json \
> "$ASC_ANALYTICS_DIR/inventory.json" \
2> "$ASC_ANALYTICS_DIR/inventory.stderr"
Always use --paginate; asc follows Apple-provided report and instance next
links. Do not reconstruct, alter, or follow pagination URLs manually.
5. Download every segment
Parse inventory.json structurally. For every selected instance, enumerate all
segments and retain each segment's exact ID, sizeInBytes, and checksum for
verification. Do not print downloadUrl.
Download each segment by its request, instance, and segment IDs. Use a filename
derived only from the segment ID and keep the compressed bytes intact. Analytics
reports are tab-delimited text, so use .txt.gz rather than implying CSV:
SEGMENT_FILE="$ASC_ANALYTICS_DIR/segments/$SEGMENT_ID.txt.gz"
asc --profile "$ANALYTICS_PROFILE" analytics download \
--request-id "$REQUEST_ID" \
--instance-id "$INSTANCE_ID" \
--segment-id "$SEGMENT_ID" \
--output "$SEGMENT_FILE" \
> /dev/null \
2>> "$ASC_ANALYTICS_DIR/download.stderr"
Do not use --decompress before verification. If an instance has multiple
segments, download every one; never treat the first segment as the whole report.
6. Verify the downloaded files
For each file, compare the compressed byte count with sizeInBytes and the
lowercase MD5 digest with checksum. Use local system tools such as:
actual_size="$(wc -c < "$SEGMENT_FILE" | tr -d ' ')"
actual_md5="$(openssl dgst -md5 -r "$SEGMENT_FILE" | awk '{print tolower($1)}')"
expected_md5="$(printf '%s' "$CHECKSUM" | tr '[:upper:]' '[:lower:]')"
Require actual_size to equal sizeInBytes and actual_md5 to equal
expected_md5. On a mismatch, mark that segment failed, keep the raw error
private, and do not claim a complete collection. asc analytics download
refuses to overwrite an existing output, so retry the failed segment once to a
new path such as $ASC_ANALYTICS_DIR/segments/$SEGMENT_ID.retry-1.txt.gz. Verify
the retry independently and use it only if both checks pass. Keep the original
failed file unless the user approves its deletion. Do not parse or analyze a
file until verification succeeds.
7. Report the result
Return a concise summary containing:
- the selected processing date and granularity values;
- counts of reports, instances, expected segments, downloaded segments, and verified segments;
- whether the collection is complete;
- failed or missing segment IDs, if any, without signed URLs or report rows;
- the private output directory when appropriate for the current user session.
Do not include analytics values, signed URLs, profile names, credentials, or raw rows in a public artifact. Keep the verified files for the user's next workflow. Ask before deleting the temporary directory or any downloaded evidence.
文件元数据
name: asc-analytics-reports description: Collect, download, and verify App Store Connect Analytics reports with asc. Use when users need to discover analytics report requests, select report instances by processing date or granularity, download every segment, or verify downloaded files against Apple's size and MD5 metadata before analysis.
查看原始文本
---
name: asc-analytics-reports
description: Collect, download, and verify App Store Connect Analytics reports with asc. Use when users need to discover analytics report requests, select report instances by processing date or granularity, download every segment, or verify downloaded files against Apple's size and MD5 metadata before analysis.
---
# asc analytics reports
Collect a complete set of analytics report segments and verify the compressed
files before handing them to a separate analysis workflow. Do not interpret,
aggregate, or present the report contents as part of this skill.
## Guardrails
- Treat report inventories, signed URLs, downloaded segments, and identifiers as
confidential business data.
- Prefer an existing request. Creating a request changes App Store Connect state
and requires an Admin-authorized profile; obtain explicit user approval before
running `asc analytics request`.
- Never delete or replace a request as part of collection.
- Use `asc analytics download`; do not fetch or persist signed segment URLs
separately.
- Store private files outside the source repository with owner-only permissions.
- Do not claim the collection is complete if any expected segment is missing or
fails verification.
## 1. Verify the CLI contract
Inspect the installed command before authentication or collection:
```bash
asc analytics view --help
```
Continue only when help lists `--processing-date`, `--granularity`,
`--paginate`, and `--include-segments`. These filters require asc 3.5.0 or
newer. If either filter is absent, ask the user to upgrade. Do not substitute
the deprecated `--date` flag because it uses legacy local matching rather than
Apple's server-side processing-date filter.
## 2. Prepare private storage
Create a private temporary directory outside the repository before capturing
JSON or downloading segments:
```bash
umask 077
ASC_ANALYTICS_DIR="$(mktemp -d "${TMPDIR:-/tmp}/asc-analytics.XXXXXX")"
mkdir -m 700 "$ASC_ANALYTICS_DIR/segments"
```
Redirect command output and errors into this directory. Do not paste raw
inventory JSON or error output into chat, commits, issues, or pull requests.
## 3. Find an existing request
Resolve the app ID and selected asc profile, then list every request:
```bash
asc --profile "$PROFILE" analytics requests \
--app "$APP_ID" \
--paginate \
--output json \
> "$ASC_ANALYTICS_DIR/requests.json" \
2> "$ASC_ANALYTICS_DIR/requests.stderr"
```
Inspect the JSON structurally and select an existing usable request. Do not rely
on `--state` when discovery works without it. If no usable request exists, stop
and ask whether the user wants to create `ONGOING` or `ONE_TIME_SNAPSHOT`
access. State the target app and profile before requesting approval. After
approval, prefer `--reuse-existing` to avoid duplicates:
```bash
asc --profile "$APPROVED_PROFILE" analytics request \
--app "$APP_ID" \
--access-type "$ACCESS_TYPE" \
--reuse-existing \
--output json \
> "$ASC_ANALYTICS_DIR/request.json" \
2> "$ASC_ANALYTICS_DIR/request.stderr"
```
Do not run that command without explicit approval. Read the returned request ID
from the private JSON response before continuing:
```bash
REQUEST_ID="$(jq -er '.requestId' "$ASC_ANALYTICS_DIR/request.json")"
```
When a request was created or reused with the approved profile, set
`ANALYTICS_PROFILE="$APPROVED_PROFILE"`. For an existing request discovered
with the read-only profile, set `ANALYTICS_PROFILE="$PROFILE"`. Use that same
profile for every subsequent `analytics view` and `analytics download` call.
## 4. Discover and select report instances
First retrieve report and instance metadata without segment URLs:
```bash
asc --profile "$ANALYTICS_PROFILE" analytics view \
--request-id "$REQUEST_ID" \
--paginate \
--output json \
> "$ASC_ANALYTICS_DIR/discovery.json" \
2> "$ASC_ANALYTICS_DIR/discovery.stderr"
```
Select an available `processingDate` and the granularity requested by the user.
Accept `DAILY`, `WEEKLY`, and `MONTHLY`, individually or as a comma-separated
list. Split the input on commas, trim each token, and normalize it to uppercase.
Validate every token against that allowlist, including empty tokens. Report the
invalid input and stop before running `analytics view`; never silently discard
unsupported values or continue with an empty filter. After validation, remove
duplicates and join the remaining values with commas.
Treat `processingDate` as the date Apple processed the report, not necessarily
the period represented by its rows.
Retrieve the filtered inventory, including all segment metadata:
```bash
asc --profile "$ANALYTICS_PROFILE" analytics view \
--request-id "$REQUEST_ID" \
--processing-date "$PROCESSING_DATE" \
--granularity "$GRANULARITY" \
--paginate \
--include-segments \
--output json \
> "$ASC_ANALYTICS_DIR/inventory.json" \
2> "$ASC_ANALYTICS_DIR/inventory.stderr"
```
Always use `--paginate`; asc follows Apple-provided report and instance next
links. Do not reconstruct, alter, or follow pagination URLs manually.
## 5. Download every segment
Parse `inventory.json` structurally. For every selected instance, enumerate all
segments and retain each segment's exact ID, `sizeInBytes`, and `checksum` for
verification. Do not print `downloadUrl`.
Download each segment by its request, instance, and segment IDs. Use a filename
derived only from the segment ID and keep the compressed bytes intact. Analytics
reports are tab-delimited text, so use `.txt.gz` rather than implying CSV:
```bash
SEGMENT_FILE="$ASC_ANALYTICS_DIR/segments/$SEGMENT_ID.txt.gz"
asc --profile "$ANALYTICS_PROFILE" analytics download \
--request-id "$REQUEST_ID" \
--instance-id "$INSTANCE_ID" \
--segment-id "$SEGMENT_ID" \
--output "$SEGMENT_FILE" \
> /dev/null \
2>> "$ASC_ANALYTICS_DIR/download.stderr"
```
Do not use `--decompress` before verification. If an instance has multiple
segments, download every one; never treat the first segment as the whole report.
## 6. Verify the downloaded files
For each file, compare the compressed byte count with `sizeInBytes` and the
lowercase MD5 digest with `checksum`. Use local system tools such as:
```bash
actual_size="$(wc -c < "$SEGMENT_FILE" | tr -d ' ')"
actual_md5="$(openssl dgst -md5 -r "$SEGMENT_FILE" | awk '{print tolower($1)}')"
expected_md5="$(printf '%s' "$CHECKSUM" | tr '[:upper:]' '[:lower:]')"
```
Require `actual_size` to equal `sizeInBytes` and `actual_md5` to equal
`expected_md5`. On a mismatch, mark that segment failed, keep the raw error
private, and do not claim a complete collection. `asc analytics download`
refuses to overwrite an existing output, so retry the failed segment once to a
new path such as `$ASC_ANALYTICS_DIR/segments/$SEGMENT_ID.retry-1.txt.gz`. Verify
the retry independently and use it only if both checks pass. Keep the original
failed file unless the user approves its deletion. Do not parse or analyze a
file until verification succeeds.
## 7. Report the result
Return a concise summary containing:
- the selected processing date and granularity values;
- counts of reports, instances, expected segments, downloaded segments, and
verified segments;
- whether the collection is complete;
- failed or missing segment IDs, if any, without signed URLs or report rows;
- the private output directory when appropriate for the current user session.
Do not include analytics values, signed URLs, profile names, credentials, or raw
rows in a public artifact. Keep the verified files for the user's next workflow.
Ask before deleting the temporary directory or any downloaded evidence.
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- MIT
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安装前审查: 避免自动安装
许可证: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
工具列表来自元数据,并非已测试的兼容性;Agent 提示词是建议的交接方式。
从一个小任务开始
- 1阅读来源,确认输入、预期输出、依赖和权限。
- 2先让 Agent 提出计划,批准环境配置和费用,再进行隔离的小规模测试。
- 3检查输出和变更文件,只报告实际执行结果,并保留来源版本以便复现。
请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。
来源与使用须知
仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。
- 来源仓库
- rorkai/app-store-connect-cli-skills
- 许可证
- MIT
- 版本
- 1.0.0
- 最近 GitHub 推送
- 2026年8月23日
- 目录更新于
- 2026年9月3日
版本来自目录元数据,使用前请核实来源发布记录。
质量
74/100
强
信任
67/100
仅限沙盒
审计
79/100
需审查
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- 结果
- —
复制不等于安装。安装数需有成功安装回报,不代表全面的质量保证。
Agent 接入
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
更多详情
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"tier": "unproven",
"label": "Needs first agent run",
"summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
"metrics": {
"totalOutcomes": 0,
"successfulOutcomes": 0,
"failedOutcomes": 0,
"installAttempts": 0,
"installSuccessRate": null,
"successRate": null,
"recentSuccessRate": null,
"recentFailureRate": null,
"riskBlocked": 0,
"setupRequired": 0,
"notRelevant": 0,
"avgOutputQuality": null,
"avgTimeToUsefulMs": null,
"productionOutcomes": 0,
"humanReviewRequired": 0,
"uniqueAgents": 0,
"lastOutcomeAt": null
},
"signals": [],
"penalties": [
"No real agent outcome evidence yet"
]
},
"audit": {
"score": 79,
"risk_level": "needs_review",
"risk_label": "Needs review",
"warnings": [
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"Dependency/runtime risk: command execution surface, credential or environment access",
"Permission surface: secrets or environment access, shell or command execution"
]
},
"safety_gate": {
"tier": "blocked",
"label": "Blocked for auto-install",
"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 74,
"label": "Strong"
},
"supply": {
"track": "Data, BI, and analytics",
"scenario": "Data analysis",
"maintenance": "2mo since push",
"risk": "Needs review"
},
"alternative_skills": [],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"high-compliance environments without internal security review",
"No major risk signals from current metadata",
"High-risk permission hints: Shell or command execution, Secrets or environment access",
"Dependency or permission surface needs review",
"Permission surface may require sandboxing",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution"
],
"agent_contract": {
"task_input": "Use asc-analytics-reports in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 75/100 Strong shortlist",
"Audit: 79/100 Needs review",
"Safety: 39/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "rorkai-asc-analytics-reports (asc-analytics-reports)",
"install_command": "npx skills add rorkai/app-store-connect-cli-skills --skill asc-analytics-reports",
"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": "rorkai-asc-analytics-reports",
"task": "Use asc-analytics-reports 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/rorkai-asc-analytics-reports",
"api": "https://www.openagentskill.com/api/agent/skills/rorkai-asc-analytics-reports",
"audit": "https://www.openagentskill.com/skills/rorkai-asc-analytics-reports/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=rorkai-asc-analytics-reports&task=Use%20asc-analytics-reports%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20asc-analytics-reports%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20asc-analytics-reports%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/rorkai-asc-analytics-reports/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/rorkai-asc-analytics-reports"
}
}创作者工具
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此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- rorkai
- 收录方
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[](https://www.openagentskill.com/skills/rorkai-asc-analytics-reports/audit)
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