BD headhunter-pro
猎头工具包 v21.0：AI 驱动的端到端招聘工作流——12 阶段商业闭环，快速指令全覆盖，skill.yml 输入契约对齐
猎头工具包 v21.0：AI 驱动的端到端招聘工作流——12 阶段商业闭环，快速指令全覆盖，skill.yml 输入契约对齐
As a process D 38/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Risky intent
intent-offensive-securitySKILL.md:1013Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (documentation table row)| 安全 | `security pentest vulnerability` | Trivy, Falco, Wazuh |
table
Files scanned: 22. 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") - warning
body-longSKILL.md body ≈ 21218 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "description_en"
Process rating: all ten parameters 38/100
- 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
- 10Execution cost. Instruction body is 21218 tokens: crowds the task out of the window
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 659 steps
- 100Consistency. Name and required fields are in place
- low 10 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 62: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -299 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 270 headings
- +3Step-by-step instructions: 659 items
- +4Has examples (127 code blocks)
- +4Reference files are cited in the instructions (10 of 10)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 58.
External checks
ClawHub: suspicious
The skill is a recruiting assistant, but its documents include under-disclosed external sourcing, recurring monitoring, outbound follow-up, broad memory access, and sensitive candidate profiling that need review before installation.
LLM: suspicious (high) · 10 Sept 2026