SKILLEMALL.ai

BF sn-deepresearch-cli

一键启用 SenseNova-Skills-DeepResearch,用于行业与市场研究、竞品分析、政策或技术调研、商业尽调、趋势分析、方案对比、事实核查,以及研究报告、白皮书等交付场景。用户提出深度研究、调研、调查、尽调、research/deepresearch,或任务需要跨来源取证、多维度比较和交叉验证时主动使用;Skill 会完成环境检查、SenseNova-Skills-DeepResearch 安装或升级、Harness 与 Search/Camofox 准备、参数确认、研究启动和 Web 进度提示。简单常识问答、单一来源整理和纯文字润色不使用。

ClawHub Agent Skills author: SenseNova-Skills v2026.9.12 MIT-0 3 files body ≈ 1 920 tokens Open the sourceclawhub.ai analyzed 3 d ago

一键启用…

As a process F 40/100 · Will not run — References files that are not bundled: scripts/build_npm_package.py

IntegrationWordSoftware developmentData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
F
40/100
Will not run
References files that are not bundled: scripts/build_npm_package.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 3. 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")
  • warning missing-ref reference to a missing file: scripts/build_npm_package.py

Process rating: all ten parameters 40/100

Will not run. References files that are not bundled: scripts/build_npm_package.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/build_npm_package.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 21 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1920 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (8 tags): a typed call is more reliable

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
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +3Description length 282: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (11 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
The skill’s research purpose is coherent, but it deserves review because it can trigger broad networked research workflows and install mutable global npm packages.
LLM: suspicious (medium) · 11 Sept 2026