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概要と使いどころ
Supports research proposal preparation and review for NSF, NIH, DOE, DARPA, and Taiwan NSTC, including opportunity-specific requirements, aims, review criteria, budgets, broader impacts, forms, and resubmissions. Use for investigator-authored grant development, compliance matrices, and proposal critiques.
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Drafts, revises, and audits scientific manuscripts or reports with explicit evidence provenance, reporting-guideline coverage, authorship accountability, confidentiality controls, and local consistency checks. Use for manuscript sections, references, declarations, tables, figures, or submission preparation when scientific accuracy and traceability matter.
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Prepares and launches nf-core/pacsomatic matched tumor-normal PacBio HiFi genomics workflows from unaligned BAM inputs. Supports samplesheet generation, pinned Nextflow launch artifacts, local checks, LSF/Slurm/PBS Pro/SGE launcher submission, and startup troubleshooting. Use for pacsomatic run preparation and execution, not general short-read somatic analysis or medical imaging PACS.
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Resolves free-text scientific labels to ontology term IDs and validates existing CURIEs against the EBI Ontology Lookup Service (OLS4). Also looks up prefixes in Bioregistry, resolves compact identifiers via Identifiers.org, maps lab shorthand with ZOOMA, and builds Ontobee term pages. Use whenever an ontology identifier must be produced or checked - annotating tissue, cell type, disease, phenotype, assay, chemical, organism, sex, or developmental stage fields; preparing metadata for GEO, ENA, BioSamples, CELLxGENE, HCA, or ISA-Tab submission; auditing a metadata table of term IDs; checking whether a term is obsolete and what replaced it; or deciding HPO vs HP. Triggers include "ontology term", "ontology ID", "CURIE", "controlled vocabulary", "UBERON", "CL:", "MONDO", "HPO", "EFO", "ChEBI", "NCBITaxon", "GO term", "PATO", "Zooma", "Bioregistry", "Identifiers.org", "Ontobee", "annotate this tissue/cell type/disease", and any request to emit or verify an identifier shaped like PREFIX:0001234.
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。
Draft or restructure scientific manuscript arguments, sections, and initial-submission materials from author-provided evidence. Use for 论文写作、章节起草、论证重构、正文压缩、首次投稿材料. Use nature-polishing for language-only edits to existing prose and nature-response for post-decision correspondence.
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。
Draft, audit, or revise responses to peer review, revision cover letters, and marked-manuscript or LaTeX revision packages. Use for 审稿意见回复、逐点回复、返修信、 rebuttals and edits to existing response drafts. Initial-submission materials belong to nature-writing; simulated peer review belongs to nature-reviewer.
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。
Create, revise, audit, and export manuscript scientific figures in Python or R. Use for 论文配图、科研绘图、多面板图 and submission-ready plots, or explicitly requested AI-generated graphical abstracts and mechanism schematics. Not for interactive dashboards, data cleaning, or statistics-only analysis.
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。
Find animation and video references on 1human, consult a human-agent shared library, and contribute public creations only with prior owner permission.
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Build and deploy serverless functions on AWS Lambda. Configure triggers, manage permissions, and optimize performance. Use when implementing serverless applications.
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。
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
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Access matrix of role-by-module permissions, with per-role scope, confidentiality level and SME tier, as CSV, SQL, JSON Schema or Notion on request. Use for access reviews.
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Integrate Microsoft Graph SDK into any project — .NET, TypeScript/JavaScript, or Python. Covers auth patterns (client credentials, OBO, managed identity), SDK setup, calling Graph APIs, batching, delta queries, change notifications, throttling, and permission scopes. Use when accessing Microsoft 365 data (users, mail, calendar, Teams, files, SharePoint) from any application type.
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。
Mistake-proof code so misuse cannot be expressed, rather than warning against it. Use when designing an interface, schema, or state machine and the user wants it hard to get wrong ("make invalid states unrepresentable", "so callers cannot screw it up", "type-safe API", "pit of success"); when auditing existing code for footguns ("what could bite us here", "what is easy to misuse", "poka-yoke this repo", "review this diff for ways to get it wrong"); or when a bug has recurred and the fix must close the class rather than the case ("make sure this never happens again", "this is the third time"). Especially for money, auth, permissions, deletion, migrations, and pipelines where failure is silent. Classifies every finding by what happens when the mistake occurs and how the device notices, which is what keeps it from collapsing into generic code review.
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When user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.
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Shipyard's navigator — chart a foggy effort (destination unclear, questions not yet stateable) into a map of decision tickets on the repo's issue tracker, then work the frontier one ticket per session until the way is clear, and hand the collapsed decisions to /launch as a mission brief. Wayfinding, not building: it produces decisions, never deliverables.
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。
Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior
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。
Shipyard's internal requirements intake for non-engineer contributors (support/ops) — turn a pasted chat log or verbal problem report into a five-section intent.md through numbered batch questioning with a completion gate, walk it through tracker review with harbor's four records, and hand the accepted intent to /launch as its mission brief. Produces decisions, not code.
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Shipyard's governed delivery pipeline — converge the mission, synthesize a durable spec, decompose vertical-slice tickets with blocking edges, run the frontier in parallel via team, close with verification, and report with a full decision log. Two entry gates — the yard gate (drydock audit) and the fog gate (an effort whose destination is unclear is routed to /ask-navigator before this pipeline starts). Humans own the checkpoints where there is no unique answer or the error cost is severe; agents continuously run everything repeatable and acceptable-by-evidence.
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Global macro analysis framework (central bank policy transmission / FX forecasting / geopolitical risk / capital flows), used to build macro factor signals that drive cross-asset allocation.
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Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.
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Run CloudFox's read-only Describe/List/Get enumeration (all-checks, role-trusts, secrets, endpoints, and permissions commands) to map AWS and Azure attack paths and surface exploitable misconfigurations. Use immediately after obtaining a cloud credential to build situational awareness, find exposed resources and secrets, or map sts:AssumeRole trust relationships for lateral-movement/privilege-escalation planning.
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Detect DCSync attacks (MITRE T1003.006) where adversaries abuse Active Directory replication privileges to extract password hashes, by auditing Event ID 4662 for the DS-Replication-Get-Changes GUIDs and flagging non-domain-controller accounts issuing DsGetNCChanges RPC calls. Use when hunting for credential theft via Mimikatz lsadump::dcsync or Impacket secretsdump, investigating lateral movement with domain admin credentials, or auditing AD replication permissions.
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Detect AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive policies, dangerous permission combinations, and least-privilege violations
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Deploy cloud-native deception across AWS, Azure, and GCP using decoy (honey) resources whose only purpose is to generate a high-fidelity alert the instant an attacker touches them: canary IAM access keys, permission-less decoy users/roles/service principals, honey object-storage buckets, and decoy secrets in Secrets Manager / Key Vault / Secret Manager. Wires detection through CloudTrail + EventBridge, Azure Sentinel honeytoken watchlists + Defender, and GCP Cloud Audit Logs, so any use of a decoy is routed to the SOC with near-zero false positives. Use when protecting cloud accounts and data stores, when an org has only on-prem honeypots and needs cloud coverage, when seeding fake AWS keys to catch credential theft and code-leak exposure, or when detecting cloud reconnaissance and lateral movement. Keywords: cloud deception, canary token AWS, honey S3 bucket, decoy IAM credentials, CloudTrail alert, GuardDuty, Sentinel honeytoken, decoy secret, honey service account, cloud honeypot, breach detection.
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。