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BF cue-research

Use when the user asks a research question they want Cue to run — against a saved 搭子(buddy) template or as free-form deep research. 在 AI agent 里用自然语言把调研问题交给 Cue 深研平台：自动匹配 ≤2 个搭子（或走带隐私脱敏与公开信源约束的自由式深研），确认 credits 后后台执行，取回带来源链接的报告，满意可一键沉淀为搭子。Triggers: 帮我查/调研/研究 + 主体或话题; ask Cue about X; 用 Cue 跑一下 Y; 看看哪个搭子能查 X; 把刚才那次调研存成搭子. Public-data scope only — refuse for private-data scenarios (real AML / medical / internal accounting).

ClawHub Agent Skills author: wangxiaoxu v1.0.1 MIT-0 5 files body ≈ 4 583 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

在 AI agent 里用自然语言把调研问题交给 Cue 深研平台：自动匹配 ≤2 个搭子（或走带隐私脱敏与公开信源约束的自由式深研），确认 credits 后后台执行，取回带来源链接的报告，满意可一键沉淀为搭子。Triggers: 帮我查/调研/研究 + 主体或话题; ask Cue about X; 用 Cue…

As a process F 44/100 · Will not run — References files that are not bundled: ../cue-buddy, ../cue-buddy/SKILL.md, ../community-invite.md

IntegrationAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
74
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: ../cue-buddy, ../cue-buddy/SKILL.md, ../community-invite.md
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. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Obfuscation obf-hex-escape-chain scripts/test_skill_regression.py:376
    Escaped/char-code string obfuscation (test fixture / example file; quoted — discussed, not commanded)
    b'data: {"status":"failed","error":"\xe6\x96\x87\xe4\xbb\xb6\xe5\xa4\xa7\xe5\xb0\x8f\xe8\xb6\x85\xe8\xbf\x87\xe9\x99\x90\xe5\x88\xb6 50MB"}\n',
    fixturequoted

Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../cue-buddy
  • warning missing-ref reference to a missing file: ../cue-buddy/SKILL.md
  • warning missing-ref reference to a missing file: ../community-invite.md

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: ../cue-buddy, ../cue-buddy/SKILL.md, ../community-invite.md
  • 0Tools and files. 3 referenced file(s) missing: ../cue-buddy, ../cue-buddy/SKILL.md, ../community-invite.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 5 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 4583 tokens
  • 100Steps. 42 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (6 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
  • -224 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 425: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (9 code blocks)
  • +3All 2 scripts are documented
  • +1License stated

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

External checks

ClawHub: suspicious
This skill is mostly transparent about using Cue for research, but it expands from public-data research into uploading local documents and self-updating from a remote branch, which needs Review before installation.
LLM: suspicious (high) · 11 Aug 2026