SKILLEMALL.ai

AD lingxiai-note-recording

灵犀Note录音文件查询 Skill - 查询销售录音和会议录音列表及详情。 **当以下情况时使用此 Skill**: (1) 用户要查询录音列表:「录音列表」「查录音」「销售录音」「会议录音」 (2) 用户要查看录音详情:「录音详情」「查看录音」 (3) 用户要配置灵犀 API:「配置灵犀」「连接灵犀」 (4) 用户要查询会议录音:「会议录音」「会议列表」「查会议」

ClawHub Agent Skills author: liubf v1.0.0 MIT-0 4 files body ≈ 1 301 tokens Open the sourceclawhub.ai analyzed 32 h ago

灵犀Note录音文件查询 Skill - 查询销售录音和会议录音列表及详情。 当以下情况时使用此 Skill: (1) 用户要查询录音列表:「录音列表」「查录音」「销售录音」「会议录音」 (2) 用户要查看录音详情:「录音详情」「查看录音」 (3) 用户要配置灵犀 API:「配置灵犀」「连接灵犀」 (4)…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
D
46/100
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: 4. 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")

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, python) that frontmatter does not declare
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1301 tokens
  • 100Running it twice. No mutating operations

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
  • -212 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 186: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This skill is meant to query Lingxi Note recordings, but it handles sensitive transcripts and audio links with broad default retrieval and weak credential-handling guidance.
LLM: suspicious (medium) · VirusTotal: · 5 Jun 2026