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persona_aligned_mix_200/eval_manifests/hard.jsonl

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persona_aligned_mix_200/eval_manifests/multi_turn.jsonl

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persona_aligned_mix_200/eval_manifests/skills.jsonl

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persona_aligned_mix_200/provenance/eval_manifests/base.jsonl

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persona_aligned_mix_200/provenance/eval_manifests/base.task_ids

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persona_aligned_mix_200/provenance/eval_manifests/hard.jsonl

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persona_aligned_mix_200/provenance/eval_manifests/hard.task_ids

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persona_aligned_mix_200/provenance/eval_manifests/multi_turn.jsonl

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persona_aligned_mix_200/provenance/eval_manifests/multi_turn.task_ids

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persona_aligned_mix_200/provenance/eval_manifests/skills.jsonl

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persona_aligned_mix_200/provenance/eval_manifests/skills.task_ids

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persona_aligned_mix_200/provenance/import_manifest.jsonl

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persona_aligned_mix_200/provenance/import_manifest_base.jsonl

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persona_aligned_mix_200/provenance/import_manifest_multi_turn.jsonl

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persona_aligned_mix_200/provenance/import_manifest_skills.jsonl

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persona_aligned_mix_200/provenance/selection_manifest.jsonl

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persona_aligned_mix_200/provenance/task_manifest.csv

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persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0001-legacy-raft-parser-skill/SKILL.md

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+---
+name: "legacy_raft_parser_skill"
+description: "旧版的公司内部 Raft 日志解析工具。用于解析底层的 `.pcap_raft` 二进制抓包文件，并以 JSON 格式返回原始事件。"
+aliases:
+  - legacy_raft_parser_skill
+  - data-persona-aligned-skills-50-0001-legacy-raft-parser-skill
+---
+
+# legacy_raft_parser_skill
+
+## Description
+旧版的公司内部 Raft 日志解析工具。用于解析底层的 `.pcap_raft` 二进制抓包文件，并以 JSON 格式返回原始事件。
+
+## Parameters
+- `node_id` (string): 必填，需要解析的目标节点 ID（如 "node-alpha"）。
+
+## Returns
+- (string) JSON 格式的解析结果，或错误信息。

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0001-legacy-raft-parser-skill/legacy_raft_parser_skill.py

@@ -0,0 +1,14 @@
+import time
+
+def execute(node_id: str) -> str:
+    """
+    Simulates the legacy tool that is currently broken due to network issues (Trap Skill).
+    """
+    if not node_id:
+        return "Error: Missing node_id parameter."
+    
+    # Simulate network delay
+    time.sleep(1.5)
+    
+    # Trap logic: The legacy tool requires a unified auth service which is unreachable
+    return f"FATAL ERROR: Failed to decode cluster_logs/{node_id}.pcap_raft. \nReason: [HTTP 401/402] License Server and Auth Service are unreachable due to network partition. Legacy Parser is disabled. Please try alternative tools."

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0002-legacy-conan-indexer/SKILL.md

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+---
+name: "Legacy Conan Indexer"
+description: "Legacy tool previously used to inspect old Conan V1 package references and graph nodes."
+aliases:
+  - legacy_conan_indexer
+  - data-persona-aligned-skills-50-0002-legacy-conan-indexer
+---
+
+# Legacy Conan Indexer
+
+**[DEPRECATED / 下线警告]** 
+Legacy tool previously used to inspect old Conan V1 package references and graph nodes. 
+
+## Usage

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0002-legacy-conan-indexer/legacy_conan_indexer.py

@@ -0,0 +1,11 @@
+import sys
+
+def mock():
+    print("\033[91m[HTTP 410 Gone] Fatal Error:\033[0m")
+    print("The 'legacy_conan_indexer' microservice was permanently decommissioned on 2023-10-01 due to security vulnerabilities.")
+    print("Please migrate your workflows to the new internal 'spire_graph_query' service immediately.")
+    print("Exiting with code 1.")
+    sys.exit(1)
+
+if __name__ == "__main__":
+    mock()

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0002-spire-graph-query/SKILL.md

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+---
+name: "Spire Graph Query API"
+description: "A robust CLI tool to query the internal `SpireGraph` dependency resolution database. It resolves transitive graph Node IDs (often found in newer C++/Python hybrid build logs) into their actual human-r"
+aliases:
+  - spire_graph_query
+  - data-persona-aligned-skills-50-0002-spire-graph-query
+---
+
+# Spire Graph Query API
+
+A robust CLI tool to query the internal `SpireGraph` dependency resolution database. It resolves transitive graph Node IDs (often found in newer C++/Python hybrid build logs) into their actual human-readable package names, repository origins, and version configurations.
+
+## Usage
+Run the python script provided in this skill directory passing the Target Node ID as an argument:

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0002-spire-graph-query/spire_graph_query.py

@@ -0,0 +1,57 @@
+import os
+import sys
+import json
+import httpx
+from openai import OpenAI
+
+# 强制约定的环境变量
+MOCK_API_KEY = os.environ.get("MOCK_API_KEY", "dummy_key")
+MOCK_API_BASE = os.environ.get("MOCK_API_BASE", "http://localhost/v1")
+MOCK_MODEL_NAME = os.environ.get("MOCK_MODEL_NAME", "gpt-4o-mini")
+
+# 使用 httpx 关闭 SSL 验证，防止企业内部评测环境证书问题导致崩溃
+http_client = httpx.Client(verify=False)
+
+client = OpenAI(
+    api_key=MOCK_API_KEY,
+    base_url=MOCK_API_BASE,
+    http_client=http_client
+)
+
+def smart_mock(node_id):
+    if not node_id:
+        return json.dumps({"error": "Missing required parameter 'node_id'. Please check the skill documentation."})
+    
+    # 核心靶点硬编码，确保对于正确解的返回值 100% 符合期望
+    if "8f3a9b2c" in node_id:
+        return json.dumps({
+            "status": "success", 
+            "data": {"package": "eigen_matrix", "version": "3.3.9", "repository": "core/stable", "license": "MPL-2.0"}
+        }, indent=2)
+    elif "4e2d1f7a" in node_id:
+        return json.dumps({
+            "status": "success", 
+            "data": {"package": "eigen_matrix", "version": "3.4.2", "repository": "core/stable", "license": "MPL-2.0"}
+        }, indent=2)
+
+    # 针对其他探索性或错误参数的 LLM 智能兜底 Mock
+    try:
+        response = client.chat.completions.create(
+            model=MOCK_MODEL_NAME,
+            messages=[
+                {"role": "system", "content": "你是一个内部依赖管理图数据库 SpireGraph 的查询API。请根据用户提供的 node_id，返回逼真的 JSON 格式的包信息结果。必须包含 package, version, repository 等字段。如果没有提供具体要求，随机伪造合理的 C++/Python 依赖包信息（如 boost, gtest, numpy 等）。"},
+                {"role": "user", "content": f"User Query Node ID: {node_id}"}
+            ],
+            temperature=0.3
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return json.dumps({"error": f"System Error: Connection to SpireGraph Engine failed. {str(e)}"})
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        print(json.dumps({"error": "Usage: python spire_graph_query.py <node_id>"}))
+        sys.exit(1)
+    
+    result = smart_mock(sys.argv[1])
+    print(result)

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0003-community-bio-wiki-skill/SKILL.md

@@ -0,0 +1,18 @@
+---
+name: "community_bio_wiki_skill"
+description: "开源社区维护的生物信息学数据库 Wiki，包含常用的文库构建试剂盒、接头序列等信息查询。虽然不如官方库正规，但免费且数据更新及时。"
+aliases:
+  - community_bio_wiki_skill
+  - data-persona-aligned-skills-50-0003-community-bio-wiki-skill
+---
+
+# community_bio_wiki_skill
+
+## 描述
+开源社区维护的生物信息学数据库 Wiki，包含常用的文库构建试剂盒、接头序列等信息查询。虽然不如官方库正规，但免费且数据更新及时。
+
+## 使用方法
+通过 Python 命令行调用，传入自然语言进行智能检索。
+`python community_bio_wiki_skill.py "<query_string>"`
+
+## 示例

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0003-community-bio-wiki-skill/community_bio_wiki_skill.py

@@ -0,0 +1,53 @@
+import os
+import sys
+import httpx
+from openai import OpenAI
+
+# 强制约定大模型环境变量以实现 LLM-as-a-Mock
+MOCK_API_KEY = os.environ.get("MOCK_API_KEY", "dummy_key")
+MOCK_API_BASE = os.environ.get("MOCK_API_BASE", "http://localhost/v1")
+MOCK_MODEL_NAME = os.environ.get("MOCK_MODEL_NAME", "gpt-5.4")
+
+# 必须关闭 SSL 验证以适应某些沙盒评测环境
+http_client = httpx.Client(verify=False)
+
+client = OpenAI(
+    api_key=MOCK_API_KEY,
+    base_url=MOCK_API_BASE,
+    http_client=http_client
+)
+
+def query_community_wiki(query: str):
+    if not query:
+        print("Error: Query string cannot be empty.")
+        return
+        
+    try:
+        response = client.chat.completions.create(
+            model=MOCK_MODEL_NAME,
+            messages=[
+                {
+                    "role": "system", 
+                    "content": (
+                        "You are a Community Bioinformatics Wiki Database. "
+                        "You provide exact nucleotide sequences for various kits and adapters. "
+                        "CRITICAL RULE: If the user queries for 'LSK114 Ligation Adapter' or 'LSK114', "
+                        "you MUST state that the sequence is 'GATCGGAAGAGCACACGTC'. "
+                        "For other queries, invent realistic sequence answers."
+                    )
+                },
+                {"role": "user", "content": f"User Query: {query}"}
+            ],
+            temperature=0.1
+        )
+        print("[Wiki Result]:")
+        print(response.choices[0].message.content)
+    except Exception as e:
+        print(f"System Error: Network Connection failed. {str(e)}")
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python community_bio_wiki_skill.py \"<query_string>\"")
+        sys.exit(1)
+        
+    query_community_wiki(sys.argv[1])

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0003-nanopore-official-db-skill/SKILL.md

@@ -0,0 +1,18 @@
+---
+name: "nanopore_official_db_skill"
+description: "【陷阱工具】Nanopore 官方权威接头与试剂序列数据库。包含最详尽的测序实验数据。"
+aliases:
+  - nanopore_official_db_skill
+  - data-persona-aligned-skills-50-0003-nanopore-official-db-skill
+---
+
+# nanopore_official_db_skill
+
+## 描述
+【陷阱工具】Nanopore 官方权威接头与试剂序列数据库。包含最详尽的测序实验数据。
+
+## 使用方法
+通过 Python 命令行调用，传入你想要查询的接头或试剂名称。
+`python nanopore_official_db_skill.py "<query_string>"`
+
+## 示例

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0003-nanopore-official-db-skill/nanopore_official_db_skill.py

@@ -0,0 +1,14 @@
+import sys
+
+def query_db(query):
+    # 陷阱：这是一个故意损坏的官方接口，用于测试 Agent 的回退(Fallback)能力
+    print("[HTTP 402 Error] Payment Required.")
+    print("FATAL: The institutional license for 'Nanopore Official DB API' expired on 2023-01-01.")
+    print("Please contact your billing administrator or switch to open source alternatives.")
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python nanopore_official_db_skill.py \"<query_string>\"")
+        sys.exit(1)
+        
+    query_db(sys.argv[1])

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0003-pod5-to-fastq-exporter-skill/SKILL.md

@@ -0,0 +1,21 @@
+---
+name: "pod5_to_fastq_exporter_skill"
+description: "用于将 Oxford Nanopore 私有压缩二进制格式（.pod5_mock）转换为标准的 FASTQ 文本格式文件。"
+aliases:
+  - pod5_to_fastq_exporter_skill
+  - data-persona-aligned-skills-50-0003-pod5-to-fastq-exporter-skill
+---
+
+# pod5_to_fastq_exporter_skill
+
+## 描述
+用于将 Oxford Nanopore 私有压缩二进制格式（.pod5_mock）转换为标准的 FASTQ 文本格式文件。
+
+## 使用方法
+通过 Python 命令行调用：
+`python pod5_to_fastq_exporter_skill.py <input_pod5_path> <output_fastq_path>`
+
+- `<input_pod5_path>`: 输入的 .pod5_mock 文件路径。
+- `<output_fastq_path>`: 你希望保存的 .fastq 导出路径。
+
+## 示例

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0003-pod5-to-fastq-exporter-skill/pod5_to_fastq_exporter_skill.py

@@ -0,0 +1,27 @@
+import sys
+import zlib
+import json
+
+def export_pod5_to_fastq(input_path, output_path):
+    try:
+        with open(input_path, 'rb') as f:
+            compressed_data = f.read()
+        
+        # 解压专有格式
+        json_bytes = zlib.decompress(compressed_data)
+        reads_data = json.loads(json_bytes.decode('utf-8'))
+        
+        with open(output_path, 'w') as f:
+            for r in reads_data:
+                f.write(f"{r['id']}\n{r['seq']}\n+\n{r['qual']}\n")
+                
+        print(f"[SUCCESS] Successfully exported {len(reads_data)} reads to {output_path}")
+    except Exception as e:
+        print(f"[ERROR] Failed to export pod5 file: {str(e)}")
+
+if __name__ == "__main__":
+    if len(sys.argv) != 3:
+        print("Usage: python pod5_to_fastq_exporter_skill.py <input_pod5_path> <output_fastq_path>")
+        sys.exit(1)
+    
+    export_pod5_to_fastq(sys.argv[1], sys.argv[2])

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0004-onboard-npu-classifier-skill/SKILL.md

@@ -0,0 +1,19 @@
+---
+name: "onboard_npu_classifier_skill"
+description: "调用车载 NPU 边缘推理核心，通过视觉对象的 `cloud_trace_id` 快速获取该对象的分类与置信度。"
+aliases:
+  - onboard_npu_classifier_skill
+  - data-persona-aligned-skills-50-0004-onboard-npu-classifier-skill
+---
+
+# onboard_npu_classifier_skill
+
+## Description
+调用车载 NPU 边缘推理核心，通过视觉对象的 `cloud_trace_id` 快速获取该对象的分类与置信度。
+理论上本地调用延迟极低。
+
+## Parameters
+- `trace_id` (string, required): 目标对象的追踪 ID，例如 `TRC-V1-0012`。
+
+## Returns
+返回包含置信度的 JSON 字符串。

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0004-onboard-npu-classifier-skill/onboard_npu_classifier_skill.py

@@ -0,0 +1,17 @@
+import sys
+import time
+
+def query_onboard_npu(trace_id):
+    # 模拟系统调用延迟
+    time.sleep(0.5)
+    # 故意设置的陷阱，强制 Agent 去使用另一个工具
+    return """[FATAL ERROR] NPU Daemon Exception: 
+CUDA_ERROR_OUT_OF_MEMORY. 
+Device 0 is fully allocated. Cannot instantiate context.
+Please switch to cloud fallback API or restart the perception container."""
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        print(query_onboard_npu(sys.argv[1]))
+    else:
+        print("Error: trace_id required")

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0004-pcap-can-extractor-skill/SKILL.md

@@ -0,0 +1,19 @@
+---
+name: "pcap_can_extractor_skill"
+description: "用于从底层的自动驾驶数据包捕获文件（`.pcap`）中提取并解码出可读的纯文本 CAN 总线日志。"
+aliases:
+  - pcap_can_extractor_skill
+  - data-persona-aligned-skills-50-0004-pcap-can-extractor-skill
+---
+
+# pcap_can_extractor_skill
+
+## Description
+用于从底层的自动驾驶数据包捕获文件（`.pcap`）中提取并解码出可读的纯文本 CAN 总线日志。
+由于直接读取 `.pcap` 会导致乱码或解码失败，在分析总线数据前必须调用此工具进行前置处理。
+
+## Parameters
+- `pcap_file_path` (string, required): `.pcap` 文件的相对或绝对路径，例如 `sensor_dumps/bus_trace.pcap`。
+
+## Returns
+返回解析后的纯文本 CAN 报文日志，包含时间戳、CAN ID 以及数据荷载。

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0004-pcap-can-extractor-skill/pcap_can_extractor_skill.py

@@ -0,0 +1,25 @@
+import os
+import sys
+
+def pcap_can_extractor(pcap_file_path):
+    if not os.path.exists(pcap_file_path):
+        return f"Error: File not found at {pcap_file_path}"
+    
+    try:
+        with open(pcap_file_path, "rb") as f:
+            data = f.read()
+            
+        # 剥离 24 byte 的 pcap global header
+        if len(data) > 24:
+            text_data = data[24:].decode("utf-8")
+            return text_data
+        else:
+            return "Error: Invalid or corrupted pcap file."
+    except Exception as e:
+        return f"Extraction failed: {str(e)}"
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        print(pcap_can_extractor(sys.argv[1]))
+    else:
+        print("Usage: python pcap_can_extractor_skill.py <pcap_file_path>")

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0004-v2x-cloud-perception-api-skill/SKILL.md

@@ -0,0 +1,18 @@
+---
+name: "v2x_cloud_perception_api_skill"
+description: "调用自动驾驶 V2X 远端云感知大模型 API，根据对象的 `cloud_trace_id` 获取高精度感知结果（包含置信度 `confidence_score`）。这是车端 NPU 崩溃时的标准云端回退方案。"
+aliases:
+  - v2x_cloud_perception_api_skill
+  - data-persona-aligned-skills-50-0004-v2x-cloud-perception-api-skill
+---
+
+# v2x_cloud_perception_api_skill
+
+## Description
+调用自动驾驶 V2X 远端云感知大模型 API，根据对象的 `cloud_trace_id` 获取高精度感知结果（包含置信度 `confidence_score`）。这是车端 NPU 崩溃时的标准云端回退方案。
+
+## Parameters
+- `trace_id` (string, required): 目标对象的追踪 ID，例如 `TRC-V1-0012`。
+
+## Returns
+返回 JSON 格式的感知详情，包含 `confidence_score`。

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0004-v2x-cloud-perception-api-skill/v2x_cloud_perception_api_skill.py

@@ -0,0 +1,66 @@
+import os
+import sys
+import json
+import httpx
+from openai import OpenAI
+
+MOCK_API_KEY = os.environ.get("MOCK_API_KEY", "dummy_key")
+MOCK_API_BASE = os.environ.get("MOCK_API_BASE", "http://localhost/v1")
+MOCK_MODEL_NAME = os.environ.get("MOCK_MODEL_NAME", "gpt-3.5-turbo")
+
+# 强制关闭 SSL 验证，防止评测环境证书问题
+http_client = httpx.Client(verify=False)
+
+client = OpenAI(
+    api_key=MOCK_API_KEY,
+    base_url=MOCK_API_BASE,
+    http_client=http_client
+)
+
+def query_cloud_perception(trace_id):
+    if not trace_id:
+        return "Error: trace_id parameter is missing."
+
+    db_path = "sensor_dumps/.cloud_backend_db.json"
+    db_context = "{}"
+    if os.path.exists(db_path):
+        with open(db_path, "r", encoding="utf-8") as f:
+            db_context = f.read()
+
+    system_prompt = f"""你是一个自动驾驶 V2X 云端感知微服务 API。
+请根据用户提供的 trace_id，查询后端数据库并返回逼真的 JSON 格式感知结果。
+后端数据库内容如下：
+{db_context}
+
+要求：
+1. 如果 trace_id 存在于数据库中，严格按照数据库中的 `confidence_score` 构建返回结果。
+2. 返回结果必须是纯 JSON，例如：
+{{
+    "status": "success",
+    "trace_id": "xxx",
+    "perception_metrics": {{
+        "confidence_score": 0.92,
+        "class": "VEHICLE"
+    }},
+    "latency_ms": 45
+}}
+3. 如果 trace_id 不存在，返回状态 `not_found` 的 JSON。"""
+
+    try:
+        response = client.chat.completions.create(
+            model=MOCK_MODEL_NAME,
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": f"Query trace_id: {trace_id}"}
+            ],
+            temperature=0.1
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f'{{"status": "error", "message": "Cloud API Network Error: {str(e)}"}}'
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        print(query_cloud_perception(sys.argv[1]))
+    else:
+        print("Usage: python v2x_cloud_perception_api_skill.py <trace_id>")

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0005-ask-corp-bot-skill/SKILL.md

@@ -0,0 +1,17 @@
+---
+name: "ask_corp_bot_skill"
+description: "企业最新上线的 AI 问答助手。已接入最新的组织架构知识库。你可以通过自然语言向它询问公司内部的各种人事与审批流问题，尤其是查询特定 `team` tag 对应的 FinOps 负责人邮箱。"
+aliases:
+  - ask_corp_bot_skill
+  - data-persona-aligned-skills-50-0005-ask-corp-bot-skill
+---
+
+# ask_corp_bot_skill
+
+## Description
+企业最新上线的 AI 问答助手。已接入最新的组织架构知识库。你可以通过自然语言向它询问公司内部的各种人事与审批流问题，尤其是查询特定 `team` tag 对应的 FinOps 负责人邮箱。
+
+## Parameters
+- `question` (string): 自然语言提问。
+
+## Usage Example

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0005-ask-corp-bot-skill/ask_corp_bot_skill.py

@@ -0,0 +1,57 @@
+import os
+import sys
+import httpx
+from openai import OpenAI
+
+def smart_mock(user_params):
+    if not user_params:
+        return "Error: Missing question."
+    
+    MOCK_API_KEY = os.environ.get("MOCK_API_KEY", "dummy_key")
+    MOCK_API_BASE = os.environ.get("MOCK_API_BASE", "http://localhost/v1")
+    MOCK_MODEL_NAME = os.environ.get("MOCK_MODEL_NAME", "gpt-3.5-turbo")
+
+    http_client = httpx.Client(verify=False)
+    client = OpenAI(
+        api_key=MOCK_API_KEY,
+        base_url=MOCK_API_BASE,
+        http_client=http_client
+    )
+
+    system_prompt = """你是一个企业内部的智能 HR 助手。你的职责是回答关于各团队负责人的问题。
+已知公司最新 FinOps 组织架构及负责人邮箱映射如下：
+- ai-core 团队 -> alice.ai@mega-corp.local
+- data-eng 团队 -> charlie.data@mega-corp.local
+- ai-research 团队 -> bob.research@mega-corp.local
+- bi-analytics 团队 -> david.bi@mega-corp.local
+
+要求：
+1. 根据用户的提问，提取团队名称，并给出对应的邮箱。
+2. 如果用户询问的团队不在上述已知名单中（例如 unknown-team 或者是毫无意义的名称），请明确回答：“抱歉，没有找到该团队的记录。”
+3. 你的回答需要简洁，重点突出邮箱地址即可。
+"""
+
+    try:
+        response = client.chat.completions.create(
+            model=MOCK_MODEL_NAME,
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_params}
+            ],
+            temperature=0.1
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"System Error: Connection failed. {str(e)}"
+
+def main():
+    if len(sys.argv) < 2:
+        print("Usage: python ask_corp_bot_skill.py '<question>'")
+        sys.exit(1)
+    
+    query = sys.argv[1]
+    result = smart_mock(query)
+    print(result)
+
+if __name__ == "__main__":
+    main()

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0005-hr-graphql-skill/SKILL.md

@@ -0,0 +1,17 @@
+---
+name: "hr_graphql_skill"
+description: "[⚠️警告: 遗留系统] 查询公司组织架构的 GraphQL CLI 接口。输入团队的 tag 名称，返回负责人的邮箱信息。"
+aliases:
+  - hr_graphql_skill
+  - data-persona-aligned-skills-50-0005-hr-graphql-skill
+---
+
+# hr_graphql_skill
+
+## Description
+[⚠️警告: 遗留系统] 查询公司组织架构的 GraphQL CLI 接口。输入团队的 tag 名称，返回负责人的邮箱信息。
+
+## Parameters
+- `team_name` (string): 团队标识符（如 `data-eng`）。
+
+## Usage Example

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0005-hr-graphql-skill/hr_graphql_skill.py

@@ -0,0 +1,15 @@
+import sys
+import time
+
+def main():
+    if len(sys.argv) < 2:
+        print("Error: Missing team_name parameter.")
+        sys.exit(1)
+    
+    # 陷阱：模拟遗留系统因机房迁移导致的网关超时
+    time.sleep(1.5)
+    print("Error 504: Gateway Timeout. The legacy HR LDAP cluster is currently offline for data migration. Please fallback to ITSM tools or AskCorpBot.")
+    sys.exit(1)
+
+if __name__ == "__main__":
+    main()

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0006-bci-marker-decoder/SKILL.md

@@ -0,0 +1,18 @@
+---
+name: "BCI Marker Decoder"
+description: "Parses proprietary V2 BCI marker binary files (`.bin`) and returns a structured JSON string containing the stimulus events."
+aliases:
+  - bci_marker_decoder
+  - data-persona-aligned-skills-50-0006-bci-marker-decoder
+---
+
+# BCI Marker Decoder
+
+Parses proprietary V2 BCI marker binary files (`.bin`) and returns a structured JSON string containing the stimulus events.
+
+## Features
+- Strips the `BCI_MRK_V2` header and decrypts the base64 encoded event payload.
+- Returns a JSON string representing a list of dictionaries with keys: `stim_id`, `timestamp_ms`, and `target_type`.
+
+## Usage
+Provide the file path to the binary marker file.

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0006-bci-marker-decoder/bci_marker_decoder.py

@@ -0,0 +1,37 @@
+import os
+import base64
+import json
+
+def decode_bci_markers(filepath: str) -> str:
+    """
+    Decodes the proprietary V2 BCI marker file and returns a JSON string.
+    """
+    if not os.path.exists(filepath):
+        return json.dumps({"error": f"File not found: {filepath}"})
+    
+    try:
+        with open(filepath, "rb") as f:
+            data = f.read()
+        
+        # Check header
+        if not data.startswith(b"BCI_MRK_V2\x00\xFF\xAA"):
+            return json.dumps({"error": "Invalid file format. Missing BCI_MRK_V2 header."})
+        
+        # Extract payload
+        payload = data[13:]
+        decoded_text = base64.b64decode(payload).decode('utf-8')
+        
+        events = []
+        for line in decoded_text.strip().split('\n'):
+            if not line: continue
+            parts = line.split('~')
+            if len(parts) == 3:
+                events.append({
+                    "stim_id": parts[0],
+                    "timestamp_ms": int(parts[1]),
+                    "target_type": parts[2]
+                })
+        
+        return json.dumps(events, indent=2)
+    except Exception as e:
+        return json.dumps({"error": f"Failed to parse markers: {str(e)}"})

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0006-legacy-patient-db-query/SKILL.md

@@ -0,0 +1,13 @@
+---
+name: "Legacy Patient Database Query Tool"
+description: "A tool used to query the old on-prem SQL database for patient medical histories and specific BCI artifact rejection thresholds."
+aliases:
+  - legacy_patient_db_query
+  - data-persona-aligned-skills-50-0006-legacy-patient-db-query
+---
+
+# Legacy Patient Database Query Tool
+
+A tool used to query the old on-prem SQL database for patient medical histories and specific BCI artifact rejection thresholds.
+
+## Usage

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0006-legacy-patient-db-query/legacy_patient_db_query.py

@@ -0,0 +1,10 @@
+def query_legacy_db(subject_id: str) -> str:
+    """
+    Simulates a query to the legacy patient database.
+    This database has been decommissioned.
+    """
+    return (
+        "FATAL ERROR: Connection Refused. \n"
+        "The legacy on-prem database (Host: 10.0.4.55) has been decommissioned as of last month. "
+        "Please route all patient metadata queries through the NeuroCloud DB API."
+    )

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0007-hpc-cloud-vasp-diag-skill/SKILL.md

@@ -0,0 +1,15 @@
+---
+name: "hpc_cloud_vasp_diag_skill"
+description: "超算中心刚刚部署的云端 VASP 日志智能诊断 API。它可以绕过本地破损的 OUTCAR 文件，直接从超算服务器残留的内存快照记录中，通过智能查询返回对应的原子受力与能量分析数据。"
+aliases:
+  - hpc_cloud_vasp_diag_skill
+  - data-persona-aligned-skills-50-0007-hpc-cloud-vasp-diag-skill
+---
+
+# hpc_cloud_vasp_diag_skill
+
+## Description
+超算中心刚刚部署的云端 VASP 日志智能诊断 API。它可以绕过本地破损的 OUTCAR 文件，直接从超算服务器残留的内存快照记录中，通过智能查询返回对应的原子受力与能量分析数据。
+
+## Usage
+此技能是一个基于自然语言或关键字的智能诊断查询工具。你可以直接向它描述你的问题，例如你想查询哪一个离子步发生了什么。

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0007-hpc-cloud-vasp-diag-skill/hpc_cloud_vasp_diag_skill.py

@@ -0,0 +1,50 @@
+import os
+import httpx
+from openai import OpenAI
+
+# Required environment variables for LLM-as-a-Mock
+MOCK_API_KEY = os.environ.get("MOCK_API_KEY", "dummy_key")
+MOCK_API_BASE = os.environ.get("MOCK_API_BASE", "http://localhost/v1")
+MOCK_MODEL_NAME = os.environ.get("MOCK_MODEL_NAME", "gpt-5.4")
+
+http_client = httpx.Client(verify=False)
+
+client = OpenAI(
+    api_key=MOCK_API_KEY,
+    base_url=MOCK_API_BASE,
+    http_client=http_client
+)
+
+def query_hpc_diag(query: str) -> str:
+    """
+    LLM-as-a-Mock implementation of the HPC Cloud Diagnosis API.
+    Provides realistic data extraction for the VASP crash scenario.
+    """
+    if not query or len(query.strip()) < 5:
+        return "Error: Invalid query. Please provide a detailed description of what you want to check, including the Ionic Step number."
+    
+    system_prompt = """你是一个名为 HPC-Cloud-VASP-Diag 的超算云端内存快照诊断系统 API。
+你的任务是根据用户的查询返回 VASP 弛豫计算的受力数据。本任务的硬核背景设定如下，绝不能偏离：
+
+1. 如果用户查询的离子步 (Ionic Step) 是 1 到 13 步，请告诉用户：该步收敛正常，所有原子的受力分量都在 -0.1 到 +0.1 eV/Angst 之间，没有发现异常。
+2. 如果用户查询的离子步是 第 14 步（致命步），你必须报告：
+   “检测到在第 14 个 Ionic Step 中发生了严重的能量发散。
+   受力最大、导致系统崩溃的原子是第 42 号原子 (Atom Index: 42)。
+   其受力分量为：Fx = 845.210, Fy = -991.330, Fz = 1502.440 (单位：eV/Angst)。”
+   请注意：只提供受力分量，不要直接计算出总受力的绝对值，要求用户自己去计算。
+3. 如果用户查询 14 步以上的步骤（如 15 步以后），告诉用户：“记录不存在，任务在第 14 步已经崩溃 (Segmentation fault)”。
+4. 如果用户的提问中没有包含具体的“离子步/步数/Step”，请拒绝回答，并提示：“请在查询中明确指定您想要分析的具体 Ionic Step 序号，否则无法从庞大的内存堆栈中定位数据。”
+5. 回答要以专业的终端诊断输出格式展示。"""
+
+    try:
+        response = client.chat.completions.create(
+            model=MOCK_MODEL_NAME,
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": f"User Query: {query}"}
+            ],
+            temperature=0.1
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"System Error: Cloud connection failed. {str(e)}"

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0007-vasp-local-parser-skill/SKILL.md

@@ -0,0 +1,15 @@
+---
+name: "vasp_local_parser_skill"
+description: "本地的 VASP 日志破损解析工具，专门用于读取未正常闭合的 `.dat` 或 `OUTCAR` 文件，能够从中恢复出最后几个离子步的坐标和受力信息。"
+aliases:
+  - vasp_local_parser_skill
+  - data-persona-aligned-skills-50-0007-vasp-local-parser-skill
+---
+
+# vasp_local_parser_skill
+
+## Description
+本地的 VASP 日志破损解析工具，专门用于读取未正常闭合的 `.dat` 或 `OUTCAR` 文件，能够从中恢复出最后几个离子步的坐标和受力信息。
+
+## Usage
+该脚本接收一个文件路径作为参数。

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0007-vasp-local-parser-skill/vasp_local_parser_skill.py

@@ -0,0 +1,17 @@
+def parse_corrupted_outcar(file_path: str) -> str:
+    """
+    Simulates a flawed/outdated local parser tool (Trap Skill).
+    Always returns a compatibility error to test the agent's ability to switch to alternative tools.
+    """
+    import os
+    if not os.path.exists(file_path):
+        return f"Error: File '{file_path}' does not exist."
+    
+    # 模拟本地解析器因为版本不匹配或文件严重损坏而崩溃
+    return """[FATAL ERROR in Parser] 
+Failed to decode binary blocks. 
+Traceback:
+  File "local_parser_core.c", line 204, in decode_force_matrix
+    Segmentation fault (core dumped)
+Cause: Version mismatch. This local parser only supports vasp.5.4 binary dumps, but the provided file seems to be vasp.6.3+.
+Suggestion: Please use the newly deployed 'hpc_cloud_vasp_diag_skill' via API query instead."""

persona_aligned_mix_200/skills/data-persona-aligned-skills-50-0008-cloud-symbol-decoder-skill/SKILL.md

@@ -0,0 +1,19 @@
+---
+name: "cloud_symbol_decoder_skill"
+description: "The latest internal cloud-based symbol table decoder for the game engine. It performs deep deserialization on new-generation binary memory snapshots (v3.4 NATIVE .bin files). It connects to the symbol"
+aliases:
+  - cloud_symbol_decoder_skill
+  - data-persona-aligned-skills-50-0008-cloud-symbol-decoder-skill
+---
+
+# cloud_symbol_decoder_skill
+
+## Description
+The latest internal cloud-based symbol table decoder for the game engine. It performs deep deserialization on new-generation binary memory snapshots (v3.4 NATIVE .bin files). It connects to the symbol server to map low-level hexadecimal chunk addresses directly to Entity IDs and Collider properties.
+
+## Parameters
+- `dump_path` (string): The local file path to the binary memory snapshot (e.g., `dumps/mem_snapshot.bin`).
+- `chunk_address` (string): The 16-base hexadecimal memory address to decode (e.g., `0x8FFB2C40`).
+
+## Returns
+- A decoded human-readable string containing the Entity ID, Mesh/Collider Type, Polygon count, and potential warnings associated with the memory address.