SKILLEMALL.ai

BD interview-report-generator

面试分析报告生成 - 标准化批量生成面试分析报告,按固定11章结构输出DOCX格式

ClawHub Agent Skills author: suql82 v1.0.0 MIT-0 2 files body ≈ 2 595 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. 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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "trigger"

Process rating: all ten parameters 49/100

  • 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 (interview-report-generator) differs from the folder (suql-interview-report-generator)
  • 100Tools and files. No external tools needed
  • 100Steps. 79 steps
  • 100Execution cost. Instruction body is 2595 tokens
  • 100Running it twice. No mutating operations
  • low 12 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 41: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -259 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 53 headings
  • +3Step-by-step instructions: 79 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
This skill is a coherent HR interview-report generator, but it handles sensitive candidate data without enough privacy and consent guardrails.
LLM: suspicious (high) · VirusTotal: · 29 May 2026