SKILLEMALL.ai

BF alibabacloud-analyticdb-mysql-serverless-analysis

Analyze OSS data through an Alibaba Cloud AnalyticDB for MySQL (ADB) Serverless workspace with read-only, bounded Presto SQL. Trigger only when the user explicitly mentions ADB or AnalyticDB MySQL, provides a workspaceId and an oss:// path, and asks to discover, query, or analyze data. Do not trigger for an OSS path, token, accessToken, workspace, or generic SQL question alone. After triggering, validate endpoint or regionCode, workspaceId, an explicit accessToken or ADB_ACCESS_TOKEN, OSS URI, and the analysis goal together, then choose registered Hive metadata, files(...), or hive_files(...).

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.1-beta.1 MIT-0 7 files body ≈ 6 198 tokens Open the sourceclawhub.ai analyzed 2 d ago

Analyze OSS data through an Alibaba Cloud AnalyticDB for MySQL (ADB) Serverless workspace with read-only, bounded Presto SQL.

As a process F 65/100 · Will not run — References files that are not bundled: references/how-to-implement-by-common-sdk.md

AnalyzerMySQLTerraformInfrastructureSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
F
65/100
Will not run
References files that are not bundled: references/how-to-implement-by-common-sdk.md
Tools and files w 18
0
Running it twice w 4
30
Result and completion w 14
40
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6198 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/how-to-implement-by-common-sdk.md

Process rating: all ten parameters 65/100

Will not run. References files that are not bundled: references/how-to-implement-by-common-sdk.md
  • 0Tools and files. 1 referenced file(s) missing: references/how-to-implement-by-common-sdk.md
  • 30Running it twice. 11 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 6198 tokens
  • 100Steps. 70 steps
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Failures and branches. 3 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 600: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 70 items
  • +4Has examples (13 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.

External checks

ClawHub: clean
This skill appears benign: it performs disclosed, bounded read-only Alibaba Cloud ADB queries against user-specified OSS data using a runtime token.
LLM: benign (high) · VirusTotal: · 11 Aug 2026