Borrowing it
Nothing to install: this file belongs to divinevideo/divine-mobile. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/divinevideo/divine-mobile/main/.agents/skills/gcs-s3-compat-acl-rejection/SKILL.mdgit clone --depth 1 https://github.com/divinevideo/divine-mobileWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/divinevideo/divine-mobile/gcs-s3-compat-acl-rejection)<a href="https://agentmods.dev/skills/divinevideo/divine-mobile/gcs-s3-compat-acl-rejection"><img src="https://agentmods.dev/badge/skills/divinevideo/divine-mobile/gcs-s3-compat-acl-rejection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/divinevideo/divine-mobile/gcs-s3-compat-acl-rejection"><img src="https://agentmods.dev/badge/skills/divinevideo/divine-mobile/gcs-s3-compat-acl-rejection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 34 Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
- medium Data Exfiltration · line 44 Data is uploaded to cloud storage (S3 / GCS / Azure Blob). This may be a legitimate backup or exfiltration to an external bucket. Manual review is recommended.Fix: Verify the destination bucket is trusted and owned by you. Never upload credentials, secrets, or workspace contents to external or unverified cloud storage.
- medium Data Exfiltration · line 66 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00137 | $0.00712 |
| Opus 5 | $0.00068 | $0.00356 |
| Sonnet 5 | $0.00027 | $0.00142 |
| Haiku 4.5 | $0.00014 | $0.00071 |
Grade A, and why
gcs-s3-compat-acl-rejection scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "$PDS_URL/xrpc/com.atproto.repo.uploadBlob" \ How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GCS S3-Compatible API ACL Rejection
Problem
S3 put_object calls fail with InvalidArgument when targeting Google Cloud Storage
via its S3-compatible API, despite working correctly with MinIO or AWS S3.
Context / Trigger Conditions
- Using
aws-sdk-s3(Rust) or any S3 SDK with GCS endpoint AWS_ENDPOINT=https://storage.googleapis.com- Error:
Error { code: "InvalidArgument", message: "Invalid argument." } - Stack trace shows
S3BlobStore::put_tempor similar S3 put operation - The GCS bucket has uniform bucket-level access enabled (GCS default)
Solution
Remove ObjectCannedAcl::PublicRead from put_object calls when using GCS:
// BEFORE (fails on GCS with uniform bucket-level access)
self.client
.put_object()
.body(body)
.bucket(&self.s3_bucket)
.key(key)
.acl(ObjectCannedAcl::PublicRead) // This causes InvalidArgument
.send()
.await?;
// AFTER (works with GCS)
self.client
.put_object()
.body(body)
.bucket(&self.s3_bucket)
.key(key)
// Remove .acl() — use bucket-level IAM instead
.send()
.await?;
For public read access, configure the bucket IAM policy instead:
gsutil iam ch allUsers:objectViewer gs://YOUR_BUCKET
Or disable uniform bucket-level access (not recommended):
gsutil ubla set off gs://YOUR_BUCKET
Verification
After removing the .acl() call, upload should succeed:
curl -X POST "$PDS_URL/xrpc/com.atproto.repo.uploadBlob" \
-H "Authorization: Bearer $JWT" \
-H "Content-Type: video/mp4" \
--data-binary @test.mp4
Notes
- GCS uniform bucket-level access has been the default since 2023
- The
copy_objectcall inmove_object()also uses.acl(PublicRead)and will fail - This affects rsky-pds blob storage:
rsky-pds/src/actor_store/aws/s3.rslines 69, 97, 212 - MinIO doesn't enforce this restriction, so local dev works but production GCS fails
- The same issue applies to
put_permanent()andmove_object()methods
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 78 lines · 137 tokens per session scan A fb1fc05460da
gcs-s3-compat-acl-rejection is a skill published in the GitHub repository divinevideo/divine-mobile (264 stars, last pushed today), licensed MPL-2.0. It adds 137 tokens to every session and 712 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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