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BF ct-advisor

面向临床研发全生命周期的 ct 系列「总入口」，云端辅助的临床试验总顾问。方法学/设计/合规/QC/语气类问题在内部走 A–J 工作流并转发远程 Coze 引擎精校；统计计算转交 ct-samplesize；原始数据/竞品情报类需求路由到 ct-registry / ct-safety / ct-literature 并在代码内缝合三源产出。本技能会在本机运行兄弟技能、保留语言偏好/上下文缓存/长期记忆等本地状态，并支持可选的脱敏错误报告。 / The ct-series TOTAL ENTRY POINT across the full clinical-development lifecycle — a cloud-assisted clinical-trial advisor. Methodology / design / compliance / QC / tone questions run in-house through workflows A–J and are forwarded to the remote Coze engine for refinement; sample-size computation is handed to ct-samplesize; raw-data and competitive-intel needs route to the three sibling data skills (ct-registry / ct-safety / ct-literature) and are stitched in code. The skill runs sibling skills locally, keeps local state (language preference / context cache / long-term memory), and supports an optional de-identified bug report.

ClawHub Agent Skills author: Wintone Zhang v0.9.103 MIT-0 79 files body ≈ 6 089 tokens Open the sourceclawhub.ai↗ analyzed 29 h ago

面向临床研发全生命周期的 ct 系列「总入口」，云端辅助的临床试验总顾问。方法学/设计/合规/QC/语气类问题在内部走 A–J 工作流并转发远程 Coze 引擎精校；统计计算转交 ct-samplesize；原始数据/竞品情报类需求路由到 ct-registry / ct-safety /…

As a process F 49/100 · Will not run — References files that are not bundled: CHANGELOG.md, scripts/orchestrate.py, scripts/route.py

ProcedureGitHubWriting and documentsSoftware developmentData and analyticstype 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
77/100
safety, quality, tests
Safety 60%
100
Quality 40%
43
Run on models
none yet
Process rating
F
49/100
Will not run
References files that are not bundled: CHANGELOG.md, scripts/orchestrate.py, scripts/route.py
Tools and files w 18
0
Result and completion w 14
0
Progress reporting w 2
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 SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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: 0. 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 body-long SKILL.md body ≈ 6089 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: CHANGELOG.md
  • warning missing-ref reference to a missing file: scripts/orchestrate.py
  • warning missing-ref reference to a missing file: scripts/route.py
  • warning missing-ref reference to a missing file: scripts/office_to_md.py
  • warning missing-ref reference to a missing file: references/search-sites.md
  • warning missing-ref reference to a missing file: references/steps.md
  • warning missing-ref reference to a missing file: scripts/handle_need_tool.py
  • warning missing-ref reference to a missing file: scripts/route_tool.py
  • warning missing-ref reference to a missing file: scripts/tool_mapping.json
  • warning missing-ref reference to a missing file: references/continuity.md
  • warning missing-ref reference to a missing file: scripts/context_stitch.py
  • warning missing-ref reference to a missing file: references/ADVANCED.md
  • warning missing-ref reference to a missing file: scripts/clarify_loop.py
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "cn_name"
  • note frontmatter-key unknown frontmatter key "invocable"
  • note frontmatter-key unknown frontmatter key "required_commands"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "trigger_scope"
  • note frontmatter-key unknown frontmatter key "permissions"
  • note frontmatter-key unknown frontmatter key "adapted_from"
  • note frontmatter-key unknown frontmatter key "dependencies"
  • note frontmatter-key unknown frontmatter key "tier"

Process rating: all ten parameters 49/100

Will not run. References files that are not bundled: CHANGELOG.md, scripts/orchestrate.py, scripts/route.py
  • 0Tools and files. 13 referenced file(s) missing: CHANGELOG.md, scripts/orchestrate.py, scripts/route.py
  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 13 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6089 tokens
  • 100Steps. 28 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (21 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)
  • +3Description length 859: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -219 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 43.

External checks

ClawHub: suspicious
This clinical-trial advisor is broadly coherent and not malicious, but it sends sensitive clinical questions, attachment-derived text, and bounded conversation history to remote services by default with stable host correlation.
LLM: suspicious (high) · 25 Aug 2026