BF infoseek
端到端内容智能采集与调研工作流。从行业/主题/人名/公司输入开始，自动嗅探信息源、按可信度+主题一致性+互动深度+LLM可读性四维评分门控、深度抓取（4级降级：静态/渲染/凭证/多媒体）、搜索引擎全生命周期管理（健康/配额/新鲜度自愈）、QVeris 能力路由、统一能力注册表（consent 闸控）、语义矛盾检测（共享事实槽+否定词典+极性放大）、实体识别（95+实体+多语种+别名归并）、召回增强（别名扩展/多样性合并/自适应门槛）、跨源融合分析，最终输出结构化 Markdown 报告，可选自动归档。适用：行业调研、趋势分析、竞品分析、市场研究、技术研究、内容采集、报告生成、长期知识库建设。不适用：实时新闻监控、学术文献综述、浏览器自动化爬取、即时聊天对话
端到端内容智能采集与调研工作流。从行业/主题/人名/公司输入开始，自动嗅探信息源、按可信度+主题一致性+互动深度+LLM可读性四维评分门控、深度抓取（4级降级：静态/渲染/凭证/多媒体）、搜索引擎全生命周期管理（健康/配额/新鲜度自愈）、QVeris 能力路由、统一能力注册表（consent…
As a process F 36/100 · Will not run — References files that are not bundled: scripts/mcp_tools_search.py, scripts/summarize_adapter.py, scripts/infoseek_helper.py
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 80. 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") - warning
missing-refreference to a missing file: scripts/mcp_tools_search.py - warning
missing-refreference to a missing file: scripts/summarize_adapter.py - warning
missing-refreference to a missing file: scripts/infoseek_helper.py - warning
missing-refreference to a missing file: scripts/infoseek_core_v2.py - warning
missing-refreference to a missing file: scripts/infoseek_keys_cli.py - warning
missing-refreference to a missing file: scripts/leak_scan.py - warning
missing-refreference to a missing file: scripts/infoseek_pipeline.py - warning
missing-refreference to a missing file: scripts/engine_lifecycle.py - warning
missing-refreference to a missing file: scripts/qveris_client.py - warning
missing-refreference to a missing file: scripts/public_apis_catalog.py - warning
missing-refreference to a missing file: scripts/tiered_router.py
Process rating: all ten parameters 36/100
- 0Tools and files. 11 referenced file(s) missing: scripts/mcp_tools_search.py, scripts/summarize_adapter.py, scripts/infoseek_helper.py
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (infoseek) differs from the folder (info-seek)
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 47 steps
- 100Execution cost. Instruction body is 3131 tokens
- 100Running it twice. No mutating operations
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 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
- -35 of 6 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 332: enough signal without eating the budget
- +4Structure: 36 headings
- +3Step-by-step instructions: 47 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (13 of 13)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.