SKILLEMALL.ai
RU Sign in

BF deep-research

OpenClaw 纯工作流深度调研：不绑定模型或搜索服务，把宿主工具编排成可复核流程。适合竞品、行业、选型、风险和资料研究；N 轮追问、多来源原文核验、冲突披露，交付可审计报告和证据包。

ClawHub Agent Skills author: 澄歌 v0.2.5 MIT-0 35 files body ≈ 99 tokens Open the sourceclawhub.ai↗ analyzed 29 h ago

OpenClaw 纯工作流深度调研：不绑定模型或搜索服务，把宿主工具编排成可复核流程。适合竞品、行业、选型、风险和资料研究；N 轮追问、多来源原文核验、冲突披露，交付可审计报告和证据包。

As a process F 34/100 · Will not run — weak spots: steps, result and completion, when it triggers

ReferenceAI 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
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
59
Run on models
none yet
Process rating
F
34/100
Will not run
Steps w 15
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.
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: 35. 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 "homepage"

Process rating: all ten parameters 34/100

  • 0Steps. Prose only: no discrete steps
  • 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 (deep-research) differs from the folder (deep-research-skill)
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 99 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)
  • +3Description length 93: 120–800 characters recommended
  • +4Structure: 1 headings, hard to scan
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -311 of 12 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +4Reference files are cited in the instructions (3 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.

External checks

ClawHub: clean
This is a disclosed deep-research workflow skill that writes local audit artifacts and uses host-provided search, browsing, and optional sub-agents without evidence of hidden exfiltration or destructive behavior.
LLM: benign (high) · VirusTotal: · 4 Sept 2026