BD tender-construction
招投标数据查询与分析助手，本版侧重 建筑工程 / 市政。当用户涉及以下场景时使用此 SKILL：查询招标/中标公告、搜索标讯、查找临期项目、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、推荐潜在投标供应商、查询企业工商登记信息（统一社会信用代码/注册资本/法定代表人/经营范围）、分析公司主营业务与历史中标、查询上下游客户与供应商、分析竞争对手、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、查询品牌型号历史中标单价与价格趋势、查询当前账户余额/剩余积分、市场分析/采购寻源/渠道拓展等采购与投标场景。涉及 施工、EPC、工程总承包、建设工程、市政、道路、桥梁、管网、装修、幕墙、勘察设计、监理 等方向时尤其适用。**范围约定**：本版把 建筑工程 / 市政 作为**默认检索范围**，不是限制。优先级从高到低：①用户本轮明确指定的以用户为准；②地区与行业是两个独立维度，可以叠加，本版只提供行业默认值，不覆盖用户指定的另一维度；③只有同为行业版的多个包同时存在、且用户本轮未指定行业时，才先询问再检索，不要替用户选。无论用哪种，都要在回答中说明本次实际检索的范围。
招投标数据查询与分析助手，本版侧重 建筑工程 / 市政。当用户涉及以下场景时使用此…
As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 Exfiltration
net-credential-usereferences/auto-register.md:215Credential 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=s155` 手动登录充值。
quoted
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 42/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Execution cost. Instruction body is 4181 tokens
- 100Steps. 35 steps
- 100Consistency. Name and required fields are in place
- low 16 top-level sections: this looks like several domains in one skill
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
- -225 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 509: enough signal without eating the budget
- +4Structure: 40 headings
- +3Step-by-step instructions: 35 items
- +4Has examples (20 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.