SKILLEMALL.ai
RU Sign in

BF zlbx-ai-platform

招投标全能助手，一个 SKILL 覆盖查标讯、投标决策、商机挖掘、企业背调四大能力。当用户涉及以下招投标与政企采购场景时，必须使用此SKILL：【标讯搜索】查询招标/中标公告、搜索标讯、查找临期或即将到期项目、查询拟建项目与立项审批阶段的早期商机、追踪项目各阶段进展与全流程时间线、查询Top采购单位/Top中标单位/Top中标品牌、招中标数据统计分析（按月/季/年/省份/品牌等维度）、查询品牌型号历史中标单价与价格趋势；【投标决策】判断某条标讯该不该投、评估中标概率、制定投标策略、分析投标竞争格局、投标可行性分析、废标风险与红线检查；【商机雷达】挖掘招投标早期商机、拟建项目跟踪、临期合同续约提醒、政企采购意向监控、招投标销售线索发现、商机晨报；【企业情报】从招投标视角背调客户/供应商/竞对，包括历史中标记录与战绩、主营业务与优势品类、上下游合作客户与供应商关系、投标对手分析、同类项目经验与履约能力证据分析；【账户】查询本平台账户余额与剩余积分。本 SKILL 只解决招投标与政企采购领域的问题；与招投标无关的通用写作、通用市场调研、个人银行账户等场景不适用。若用户已单独安装了本平台的单条线专用 SKILL（标讯查询/投标决策/商机雷达/企业情报），纯单一场景优先用专用版，跨线组合任务用本全能版。

ClawHub Agent Skills author: Bailian v1.1.0 MIT-0 23 files body ≈ 1 591 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

招投标全能助手，一个 SKILL…

As a process F 35/100 · Will not run — References files that are not bundled: references/<线>/, scripts/<线>/render_report.py, references/<线>/overview.md

ProcedureProcurementtype 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
81/100
safety, quality, tests
Safety 60%
93
Quality 40%
64
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/<线>/, scripts/<线>/render_report.py, references/<线>/overview.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. 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 · 7

✓ No critical or high findings

Medium and low: 7
  • low Exfiltration net-credential-use references/auto-register.md:215
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    **如果当前 api_key 来自 `$ZLBX_API_KEY`**：跳过 SID 流程，提示用户访问 `https://ai.zhiliaobiaoxun.com/?ch=s142` 手动登录充值。
    quoted
  • low Obfuscation obf-base64-blob scripts/bid-decision/render_report.py:71
    Long base64-looking blob (quoted — discussed, not commanded)
    _LOGO_B64 = "iVBO…B5x
    quoted
  • low Secrets in code secret-high-entropy-token scripts/bid-decision/render_report.py:71
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    _LOGO_B64 = "iVBO…B5x
    quoted
  • low Obfuscation obf-base64-blob scripts/company-intel/render_report.py:93
    Long base64-looking blob (quoted — discussed, not commanded)
    _LOGO_B64 = "iVBO…B5x
    quoted
  • low Secrets in code secret-high-entropy-token scripts/company-intel/render_report.py:93
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    _LOGO_B64 = "iVBO…B5x
    quoted
  • low Obfuscation obf-base64-blob scripts/opportunity-radar/render_report.py:64
    Long base64-looking blob (quoted — discussed, not commanded)
    _LOGO_B64 = "iVBO…B5x
    quoted
  • low Secrets in code secret-high-entropy-token scripts/opportunity-radar/render_report.py:64
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    _LOGO_B64 = "iVBO…B5x
    quoted

Files scanned: 23. 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: references/<线>/
  • warning missing-ref reference to a missing file: scripts/<线>/render_report.py
  • warning missing-ref reference to a missing file: references/<线>/overview.md

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/<线>/, scripts/<线>/render_report.py, references/<线>/overview.md
  • 0Tools and files. 3 referenced file(s) missing: references/<线>/, scripts/<线>/render_report.py, references/<线>/overview.md
  • 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
  • 100Steps. 27 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1591 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 555: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

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

External checks

ClawHub: suspicious
The skill is a coherent procurement assistant, but it needs Review because it preserves login-bypass links in shareable reports and handles local credentials and device identifiers with incomplete safeguards.
LLM: suspicious (high) · 8 Sept 2026