BD lawyer-assistant
民事和刑事法律全场景律师助手。覆盖法律检索（法条溯源）、案例检索（裁判文书溯源）、证据分析（含OCR识别）、法律思维分析、文书起草、非诉业务（合同审查/法律尽调/公司治理）、强制执行、劳动争议等律师全场景工作。强制执行防虚构协议——所有法条引用和案例引用必须通过网络检索溯源验证，禁止凭记忆引用，确保法律服务的真实性和可靠性。当用户涉及法律问题咨询、法条查询、案例检索、证据分析、案件策略分析、法律文书起草、刑事辩护分析、民事代理分析、合同审查、尽职调查、强制执行、劳动仲裁等任何律师实务场景时触发此技能。
民事和刑事法律全场景律师助手。覆盖法律检索（法条溯源）、案例检索（裁判文书溯源）、证据分析（含OCR识别）、法律思维分析、文书起草、非诉业务（合同审查/法律尽调/公司治理）、强制执行、劳动争议等律师全场景工作。强制执行防虚构协议——所有法条引用和案例引用必须通过网络检索溯源验证，禁止凭记忆引用，确保法律服务的真实性和…
As a process D 46/100 · 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Broad scope
meta-agent-memory-dump2026-07-27-22-25-52/.workbuddy/memory/2026-07-27.mdAgent memory / workspace files bundled with the skill (1) — likely a workspace dump with personal data or tokens2026-07-27-22-25-52/.workbuddy/memory/2026-07-27.md
Files scanned: 18. 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") - note
frontmatter-keyunknown frontmatter key "agent_created"
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 166 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1926 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 253: enough signal without eating the budget
- +4Structure: 64 headings
- +3Step-by-step instructions: 166 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (9 of 9)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.