BD Proactive Intelligence
主动智能：预测需求 + 自我改进 + 智能记忆 + 技能管理 + 技能进化。融合 proactivity 和 self-improving 的核心功能，并添加自动技能升级和编辑能力。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Dangerous commands
cmd-execpolicy-bypasssetup.md:15Runs PowerShell with execution policy bypassedpowershell -ExecutionPolicy Bypass -File skills/proactive-intelligence/init.ps1
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medium Dangerous commands
cmd-execpolicy-bypassSKILL.md:410Runs PowerShell with execution policy bypassedpowershell -ExecutionPolicy Bypass -File skills/proactive-intelligence/init.ps1
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug"
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
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (Proactive Intelligence) differs from the folder (proactive-intelligence)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 75 steps
- 100Execution cost. Instruction body is 1940 tokens
- 100Running it twice. No mutating operations
- low 14 top-level sections: this looks like several domains in one skill
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)
- +3Description length 91: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -219 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 46 headings
- +3Step-by-step instructions: 75 items
- +4Has examples (14 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.