AD execute-verify-report
Execute-Verify-Report 三步法工具 — 强制AI遵循"执行→验证→报告"流程，杜绝"说做了其实没做"、"完成了但不验证"等问题。基于STANDING-ORDERS核心原则设计。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
AnalyzerData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 41/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (execute-verify-report) differs from the folder (evr-xiaobai)
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 100Steps. 4 steps
- 100Execution cost. Instruction body is 808 tokens
- 100Progress reporting. Reports progress
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 98: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +4Structure: 17 headings
- +3Step-by-step instructions: 4 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.
External checks
ClawHub: clean
The supplied scanner context does not show malicious or suspicious behavior, and the available workspace evidence does not reveal a purpose-mismatched skill payload.
LLM: benign (medium) · VirusTotal: · 29 May 2026