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- 作者仓库星标 49
- 许可证 MIT
- 作者更新于 实时读取
- 作者仓库 dimcli
- 领域
- 通用
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 94 / 100 · 已通过审计
- 作者 / 版本 / 许可
- @digital-science · MIT
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 即装即用
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- Python
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- 网络行为
- 允许外网请求
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: dimcli
description: Query the Dimensions Analytics API using the dimcli CLI tool. Use when the user wants to search…
category: 通用
runtime: Python
---
# dimcli 输出预览
## PART A: 任务判断
- 适用问题:通用任务拆解、检查和交付。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Workflow / Query Structure / Output Format”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于通用任务拆解、检查和交付,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Workflow / Query Structure / Output Format”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、会按任务需要访问外部网络、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;会按任务需要访问外部网络;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件。
先用一个小任务确认它会围绕“Workflow / Query Structure / Output Format”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: dimcli
description: Query the Dimensions Analytics API using the dimcli CLI tool. Use when the user wants to search…
category: 通用
source: digital-science/dimcli
---
# dimcli
## 什么时候使用
- 把通用方向的常用动作沉淀成 Agent 可调用的技能 适合处理通用任务拆解、检查、交付和复盘,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代的步骤;通常不需要额外…
- 面向通用任务拆解、检查和交付,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Workflow / Query Structure / Output Format」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;会按任务需要访问外部网络;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "dimcli" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Workflow / Query Structure / Output Format
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Python | 读取文件、写入/修改文件 | 会按任务需要访问外部网络
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Dimcli Skill
Query the Dimensions Analytics API via dimcli -q "..." and present results with clickable Dimensions URLs.
Workflow
- Identify the source and intent from the user's request
- Construct a valid DSL query — always include
idso URLs can be built - Run:
dimcli -q "<query>" -f json - Parse JSON and present a numbered list with title, key metadata, and Dimensions URL
- Offer follow-ups: refine, export to CSV, fetch more records
If unsure about available fields, run dimcli -q "describe schema" first.
DSL grammar and URL patterns: See grammar.md and urls.md.
Query Structure
search <source> [for "<keywords>"] [where <filters>] return <source>[field1+field2+...] [limit N] [sort by <field>]
Always include id in return fields. Use [basics] for a standard field set.
Output Format
Present results as a numbered list:
1. **Title of the work** (2023)
Journal: Nature | Cited by: 142
https://app.dimensions.ai/details/publication/pub.1234567890
2. ...
Summarise after the list: total found, date range, notable patterns.
Flags
| Flag | Use case |
|---|---|
-f json |
Default — structured data |
-f csv --nice |
Clean tabular export |
-f df |
Formatted terminal table |
-f df --html |
HTML table with hyperlinks |
Advanced
- Large results: API returns max 1000/call (50k with pagination). Suggest narrowing filters or using
query_iterative()in Python. - Schema lookup:
dimcli -q "describe schema" - Export:
dimcli -q "..." -f csv --nice > results.csv
Subcommand: profile <grid_id>
Generate a full profile report for an organisation, given its GRID ID (format: grid.XX).
Workflow
Run all queries sequentially (never in parallel — concurrent calls cause session conflicts).
Step 1 — Fetch organisation metadata:
dimcli -q "search organizations where id = \"<grid_id>\" return organizations[acronym+city_name+country_code+country_name+dimensions_url+established+external_ids_fundref+hierarchy_details+id+isni_ids+latitude+linkout+longitude+name+organization_child_ids+organization_parent_ids+organization_related_ids+ror_ids+status+types+ultimate_parent_id+wikidata_ids+wikipedia_url]" -f json 2>/dev/null
Note:
organizations[all]is not valid — always enumerate fields explicitly.
Step 2 — Count documents per source:
Run each query below sequentially. Extract _stats.total_count from the JSON.
# Publications
dimcli -q "search publications where research_orgs = \"<grid_id>\" return publications limit 1" -f json 2>/dev/null
# Grants
dimcli -q "search grants where research_orgs = \"<grid_id>\" return grants limit 1" -f json 2>/dev/null
# Datasets
dimcli -q "search datasets where research_orgs = \"<grid_id>\" return datasets limit 1" -f json 2>/dev/null
# Clinical Trials
dimcli -q "search clinical_trials where research_orgs = \"<grid_id>\" return clinical_trials limit 1" -f json 2>/dev/null
# Patents — NOTE: uses 'assignees', not 'research_orgs'
dimcli -q "search patents where assignees = \"<grid_id>\" return patents limit 1" -f json 2>/dev/null
# Reports
dimcli -q "search reprots where research_orgs = \"<grid_id>\" return reports limit 1" -f json 2>/dev/null
# Policy Documents — NOTE: uses 'publisher_org', not 'research_orgs'
dimcli -q "search policy_documents where publisher_org = \"<grid_id>\" return policy_documents limit 1" -f json 2>/dev/null
Each source uses a different field name to filter by organisation:
Source Filter field publications, grants, datasets, clinical_trials research_orgspatents assigneespolicy_documents publisher_org
Step 2b — Count documents where org is a funder:
# Publications (as funder)
dimcli -q "search publications where funders = \"<grid_id>\" return publications limit 1" -f json 2>/dev/null
# Grants (as funder) — NOTE: uses 'funder_orgs', not 'funders'
dimcli -q "search grants where funder_orgs = \"<grid_id>\" return grants limit 1" -f json 2>/dev/null
# Datasets (as funder)
dimcli -q "search datasets where funders = \"<grid_id>\" return datasets limit 1" -f json 2>/dev/null
# Clinical Trials (as funder)
dimcli -q "search clinical_trials where funders = \"<grid_id>\" return clinical_trials limit 1" -f json 2>/dev/null
# Patents (as funder)
dimcli -q "search patents where funders = \"<grid_id>\" return patents limit 1" -f json 2>/dev/null
# Reports (as funder) — NOTE: uses 'funder_orgs', not 'funders'
dimcli -q "search reports where funder_orgs = \"<grid_id>\" return reports limit 1" -f json 2>/dev/null
Step 3 — Piping to Python:
Always redirect stderr with 2>/dev/null before piping to Python. The CLI prints
"Reusing cached session." to stdout, which breaks JSON parsing if included.
dimcli -q "..." -f json 2>/dev/null | python3 -c "import json,sys; d=json.load(sys.stdin); print(d['_stats']['total_count'])"
Output Format
Print the profile as a markdown report:
# Organisation Profile: <Name> (<acronym>)
**GRID ID:** `<id>` | **Status:** <status> | **Type:** <types> | **Established:** <year>
## Location
- City: <city>, <country>
- Coordinates: <lat>, <lon>
## Links
- Website: <linkout>
- Wikipedia: <wikipedia_url>
- Dimensions: <dimensions_url>
## External Identifiers
- ROR: <ror_ids>
- ISNI: <isni_ids>
- Wikidata: <wikidata_ids>
- FundRef IDs: <external_ids_fundref>
## Hierarchy
- Ultimate parent: <ultimate_parent_id>
- Parent orgs: <organization_parent_ids>
- Child orgs: <organization_child_ids>
- Related orgs: <organization_related_ids>
## Document Counts (as Research Org)
| Source | Count | Dimensions URL |
|--------|------:|----------------|
| Publications | N | https://app.dimensions.ai/discover/publication?and_facet_research_org=<grid_id> |
| Grants | N | https://app.dimensions.ai/discover/grant?search_mode=content&or_facet_research_org=<grid_id> |
| Datasets | N | https://app.dimensions.ai/discover/dataset?and_facet_research_org=<grid_id> |
| Clinical Trials | N | https://app.dimensions.ai/discover/clinical_trial?and_facet_research_org=<grid_id> |
| Patents | N | https://app.dimensions.ai/discover/patent?and_facet_research_org=<grid_id> |
| Reports | N | https://app.dimensions.ai/discover/technical_report?and_facet_research_org=<grid_id> |
| Policy Documents | N | https://app.dimensions.ai/discover/policy_document?and_facet_research_org=<grid_id> |
| **Total** | **N** | |
## Document Counts (as Funder)
| Source | Count | Dimensions URL |
|--------|------:|----------------|
| Publications | N | https://app.dimensions.ai/discover/publication?or_facet_funder=<grid_id> |
| Grants | N | https://app.dimensions.ai/discover/grant?or_facet_funder=<grid_id> |
| Datasets | N | https://app.dimensions.ai/discover/data_set?or_facet_funder=<grid_id> |
| Clinical Trials | N | https://app.dimensions.ai/discover/clinical_trial?or_facet_funder=<grid_id> |
| Patents | N | https://app.dimensions.ai/discover/patent?or_facet_funder=<grid_id> |
| Reports | N | https://app.dimensions.ai/discover/technical_report?or_facet_funder=<grid_id> |
| **Total** | **N** | |
Export
If the user asks to export, save the report to <grid_id>_profile.md using the Write tool.
Confirm the file path after saving.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核