AC alibabacloud-oss-quota-throttling-diagnosis
Read-only OSS QPS/bandwidth quota and throttling diagnostics. Use when requests persistently hit 503/SlowDown or clients time out with no server errors. Covers watermark guidance, a throttling attribution decision tree, optimization (concurrency, prefix hashing, backoff), quota-increase guidance, ActiveRequestLimitExceeded concurrency throttling, and resource pool QoS / dedicated bandwidth consultation. Triggers: "QPS limit exceeded", "bandwidth saturated", "timeout without server errors", "persistent SlowDown 503", "quota increase request", "TotalQpsLimitExceeded", "x-oss-qos-delay-time", "ActiveRequestLimitExceeded", "resource pool QoS", "dedicated bandwidth". Not for one-off SlowDown / single-request error codes, client-tool connection timeouts, transfer acceleration selection, endpoint errors, or billing (use the matching OSS diagnosis skill); never applies changes.
Read-only OSS QPS/bandwidth quota and throttling diagnostics.
As a process C 58/100 · Has gaps — weak spots: result and completion, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6038 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 58/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6038 tokens
- 85Steps. 54 steps, 1 vague phrases
- 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
- low 16 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 tags): a typed call is more reliable
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
- +3Description length 882: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 10 example trigger phrases
- +4Description says when NOT to use the skill
- +4Structure: 23 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.