「db」の検索結果

Point Aeon at a service's /feedback endpoint - pull what agents reported (bugs, missing features), triage and cluster it, then build the best accepted request as a PR for a human to approve.

日本語の概要は準備中です。原文の説明を表示しています。

编写Python脚本，实现每天定时从MongoDB获取数据，进行Gzip压缩，并通过HTTP POST请求同步到指定URL，同时处理BytesIO二进制传输错误。

日本語の概要は準備中です。原文の説明を表示しています。

Apply MongoDB data-modeling, indexing, and query rules from access patterns. Use when designing schemas, choosing embed vs reference, or tuning MongoDB query behavior.

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This skill should be used only when the user explicitly asks to use `$ralph-specum-feedback`, or explicitly asks Ralph Specum in Codex to draft or submit feedback.

日本語の概要は準備中です。原文の説明を表示しています。

Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.

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Static and dynamic malware analysis, YARA rule generation, sandbox configuration, behavioral profiling, and malware family classification

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Writes you a ready-to-use script for a feedback or hard conversation, then rehearses the pushback. Use when you need to give tough feedback, confront a peer, tell a report they are underperforming, deny a promotion, prepare to fire someone, say no to your boss, ask for feedback, or repair a conversation that went badly. Draws on 66 Lenny's Podcast guests including Kim Scott, Carole Robin and Alisa Cohn.

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Cross-reference compound IDs across 20+ databases (ChEMBL, DrugBank, PubChem, ChEBI, PDB, SureChEMBL, HMDB, DrugCentral, BindingDB) via UniChem REST API. Resolve InChIKeys to source IDs, translate between source-specific IDs, find structurally related compounds by connectivity. POST with a JSON body for all cross-reference queries; only /sources is GET. No auth required.

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Query RCSB PDB (200K+ structures) via the public REST + GraphQL APIs with plain `requests` (no SDK). Search by text, attribute, sequence, or 3D structure similarity (Search API); retrieve metadata via GraphQL (Data API); download PDB/mmCIF from files.rcsb.org. For AlphaFold predictions use alphafold-database-access; for protein sequences only use uniprot-protein-database.

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smina molecular docking CLI. AutoDock Vina fork with customizable scoring functions, native SDF/MOL2/PDB ligand input, autoboxing, local energy minimization, and per-atom score breakdowns. Pipeline: receptor PDBQT prep -> ligand prep (RDKit/OpenBabel) -> dock via autobox or explicit grid -> rescore/minimize with custom scoring -> rank poses by affinity. Choose smina over Vina when you need custom scoring terms (--custom_scoring), local optimization of an existing pose (--local_only), per-atom contributions (--atom_term_data), or SDF/MOL2 ligands without manual PDBQT conversion. For unknown binding sites use diffdock; for the Python-bindings/Vinardo workflow use autodock-vina-docking.

日本語の概要は準備中です。原文の説明を表示しています。

Access AlphaFold DB's 200M+ predicted structures by UniProt ID. Download PDB/mmCIF, analyze pLDDT/PAE, bulk-fetch proteomes via Google Cloud. For experimental structures use PDB; for prediction use ColabFold or ESMFold.

日本語の概要は準備中です。原文の説明を表示しています。

Query InterPro REST API for protein domain architecture, family classification, and member-DB integration. Search entries, retrieve a protein's domains, list family members, get taxonomic distribution, link to PDB. Unifies Pfam, PANTHER, PIRSF, PRINTS, PROSITE, SMART, CDD, NCBIfam. Use uniprot-protein-database for sequences; pdb-database for 3D structures.

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Parse HMDB (Human Metabolome Database) local XML for metabolite info, chemical properties, biological context, disease links, spectra, and cross-DB mapping. No REST API — uses ~6 GB XML download. Use drugbank-database-access for drugs; pubchem-compound-search for live lookups.

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Provides AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.

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Provides Amazon DynamoDB patterns using AWS SDK for Java 2.x. Use when creating, querying, scanning, or performing CRUD operations on DynamoDB tables, working with indexes, batch operations, transactions, or integrating with Spring Boot applications.

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Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user mentions: "DBSQL", "Databricks SQL", "SQL warehouse", "SQL scripting", "stored procedure", "CALL procedure", "materialized view", "CREATE MATERIALIZED VIEW", "pipe syntax", "|>", "geospatial", "H3", "ST_", "spatial SQL", "collation", "COLLATE", "ai_query", "ai_classify", "ai_extract", "ai_gen", "AI function", "http_request", "remote_query", "read_files", "Lakehouse Federation", "recursive CTE", "WITH RECURSIVE", "multi-statement transaction", "temp table", "temporary view", "pipe operator". SHOULD also invoke when the user asks about SQL best practices, data modeling patterns, or advanced SQL features on Databricks.

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Use DB-GPT 0.8.1 as an agentic AI data platform: install and configure provider profiles, operate its CLI and services, build agents and AWEL flows, ingest and retrieve data with RAG, call client/API surfaces, and execute code through explicitly bounded sandbox runtimes.

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Manages privacy compliance for employee background checks including criminal record processing under Art. 10 GDPR, DBS checks (UK), national law variations, and reference verification. Applies proportionality and data minimisation to pre-employment screening, defines retention limits, and addresses role-based necessity assessments. Keywords: background check, criminal record, Art. 10, DBS, pre-employment screening, vetting, data minimisation, proportionality.

日本語の概要は準備中です。原文の説明を表示しています。

360 feedback register: reviewer, subject, review cycle, visibility, due date and score, as CSV, SQL, JSON Schema or Notion on request. Use for 360 reviews or peer feedback cycles.

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Capture structured feedback on the Han skills and agents used in the current session and optionally post it as a GitHub issue to testdouble/han. Use at the end of any session where one or more han-* skills or agents ran, to rate a run, log what worked and what didn't, or submit observations for maintainers. Does not review code, investigate bugs, or research options; use code-review, investigate, or research for those. Does not provide feedback on skills or agents from non-Han plugins.

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Evidence-based investigation of issues, bugs, API calls, integrations, and other aspects of software development that need a deep dive to find the root cause and solutions. Use when you need to debug, troubleshoot, diagnose, or figure out why something is broken. Does not review code for quality or style — use code-review for auditing changes or post-code-review-to-pr for posting review feedback to GitHub. Does not assess architectural health or structural risk — use architectural-analysis for architectural concerns. Does not research open-ended options, prior art, or how something works when nothing is broken — use research for that. Does not plan the structural change a root cause calls for — use plan-a-change. Does not map bounded contexts or domain boundaries — use ddd-analysis. Does not capture feedback on Han's own skills — use han-feedback for that.

日本語の概要は準備中です。原文の説明を表示しています。

ArangoDB integration. Manage data, records, and automate workflows. Use when the user wants to interact with ArangoDB data.

日本語の概要は準備中です。原文の説明を表示しています。

AdButler integration. Manage data, records, and automate workflows. Use when the user wants to interact with AdButler data.

日本語の概要は準備中です。原文の説明を表示しています。

AbuselPDB integration. Manage data, records, and automate workflows. Use when the user wants to interact with AbuselPDB data.

日本語の概要は準備中です。原文の説明を表示しています。