GreptimeDB is an observability database that stores metrics, logs, and traces in a columnar engine over object storage, using a shared table model for the data. It is for operating telemetry backends, correlating related signals with SQL, and querying metrics with PromQL.
Borrowing it
Nothing to install: this file belongs to GreptimeTeam/greptimedb. 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/GreptimeTeam/greptimedb/main/.agents/skills/greptimedb-fuzz-ci-failure-investigation/SKILL.mdgit clone --depth 1 https://github.com/GreptimeTeam/greptimedbWrote 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/greptimeteam/greptimedb/greptimedb-fuzz-ci-failure-investigation)<a href="https://agentmods.dev/skills/greptimeteam/greptimedb/greptimedb-fuzz-ci-failure-investigation"><img src="https://agentmods.dev/badge/skills/greptimeteam/greptimedb/greptimedb-fuzz-ci-failure-investigation/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/greptimeteam/greptimedb/greptimedb-fuzz-ci-failure-investigation"><img src="https://agentmods.dev/badge/skills/greptimeteam/greptimedb/greptimedb-fuzz-ci-failure-investigation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00080 | $0.04432 |
| Opus 5.5 | $0.00032 | $0.01773 |
| Sonnet 5.5 | $0.00016 | $0.00886 |
| Haiku 4.5 | $0.00008 | $0.00443 |
Grade A, and why
greptimedb-fuzz-ci-failure-investigation scanned grade A with 0 findings 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 2mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 471 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GreptimeDB Fuzz CI Failure Investigation
Investigate failed fuzz-test jobs for GreptimeTeam/greptimedb from a local
checkout. The purpose is to download the failed job's CI output and fuzz artifacts,
then explain the likely cause by correlating the evidence with GreptimeDB source.
Always pass --repo GreptimeTeam/greptimedb to gh; local remotes may point to
forks. Keep the workflow read-only: do not rerun jobs, cancel workflows, push,
comment on PRs, or delete artifacts unless the user explicitly asks.
Scope
Use this skill for fuzz CI only. In .github/workflows/integration.yml, fuzz failures
are the CI jobs that use .github/actions/fuzz-test:
fuzztest— standalone fuzz targets.unstable-fuzztest— unstable standalone fuzz target.distributed-fuzztest— distributed cluster fuzz targets.distributed-fuzztest-with-chaos— distributed fuzz targets with Chaos Mesh.
Each matrix job runs a semantic group of targets on one prepared environment.
The group defaults to fail-fast: after the first target failure it captures that
target's diagnostics and marks the remaining targets as skipped. The workflow
strategy still uses fail-fast: false, so failures do not cancel other groups.
The reusable action .github/actions/fuzz-test/action.yaml delegates each target
to .github/scripts/run-fuzz-targets.sh. CI passes FUZZ_BIN_DIR, so the script
runs the prebuilt target executable:
<prebuilt-fuzz-binary> -max_total_time=<seconds> \
-artifact_prefix=<target-dir>/libfuzzer/
Without FUZZ_BIN_DIR, such as during local reproduction, the script falls back
to cargo fuzz run <target> --fuzz-dir tests-fuzz -D -s none with the same
libFuzzer arguments.
Failed jobs upload one group artifact. Its stable name identifies the job kind, mode, and group, for example:
fuzz-distributed-remote-wal-database-and-regular-table
The artifact contains manifest.json, summary.md, and one directory per target
under targets/<target>/. A failed distributed target can include fuzz.log,
libFuzzer reproducers, CSV/SQL traces, Kind logs, monitor dumps, and Kubernetes
state. Setup failures use targets/setup/.
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.
- 2mo ago First seen · 471 lines · 80 tokens per session scan A e509013c6db3
greptimedb-fuzz-ci-failure-investigation is a skill published in the GitHub repository GreptimeTeam/greptimedb (6,789 stars, last pushed yesterday), licensed Apache-2.0. It adds 80 tokens to every session and 4,432 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
greptimedb-fuzz-ci-failure-investigation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| greptimedb-fuzz-ci-failure-investigationGreptimeTeam/greptimedb | Skill | 6.8k | yesterday | Apache-2.0 | A | 80 | Claude Code, Codex |
| systematic-debuggingmonoscope-tech/monoscope | Skill | 2.0k | yesterday | AGPL-3.0 | A | 21 | Claude Code, Codex |
| opentelemetry-net-instrumentationAaronontheweb/dotnet-skills | Skill | 1.3k | 9d ago | MIT | A | 56 | Claude Code |
| observabilityericrisco/rsc-harness | Skill | 503 | 2d ago | MIT | A | 70 | Claude Code, Codex |
| test-driven-developmentmonoscope-tech/monoscope | Skill | 2.0k | yesterday | AGPL-3.0 | A | 17 | Claude Code, Codex |
| cloud-native-ebpf-observabilityj4flmao/agent-skills | Skill | 38 | 3d ago | MIT | A | 175 | Claude Code, Codex |
| traceway-writetracewayapp/traceway | Skill | 1.8k | 3d ago | MIT | C | 101 | Claude Code |