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概要と使いどころ
Search academic papers across arXiv, PubMed, Semantic Scholar, bioRxiv, medRxiv, Google Scholar, and more. Get BibTeX citations, download PDFs, analyze citation networks. Use for literature reviews, finding papers, and academic research.
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。
Deprecated alias. This skill was renamed to `deepline-research`. Use when a user or script still invokes `/deepline-pre-research`: immediately load and follow the `deepline-research` skill instead. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.
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。
Use when the user wants a last30days-style pre-research pass in Deepline: discover the critical public, private, CRM, workflow, social, and web data sources for a research/enrichment job; compare provider coverage; estimate Deepline credit cost; recommend the source plan before building or running the workflow; or build custom language/messaging from buyer, competitor, community, and CRM evidence. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.
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。
Opens a deliverable (talk, course module, paper, book chapter, or referee report) for AI-assisted work across sessions. Interviews the author for the manifest, then scaffolds deliverable.yml, an append-only HANDOFF.md, a numbered planning/ wiki with open questions, an inbox/ for dictated braindumps, a gitignored checks/, and the house deck template for talks. Use when starting deadline-driven work that spans sessions, or when asked to open a deliverable, set up a talk, paper, or module for the pipeline, or make a manifest. Not for one-off tasks.
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。
Start-of-session situational report for a research or code repository. Reads the handoff, log, or status files the project actually keeps, checks live git state, and reports the objective, verified baseline, open tasks, blockers, and next actions, flagging where the documents and the repository disagree. Use when resuming work after time away or before changing anything. Its end-of-session twin is finished.
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。
Reviews a whole deliverable (talk, course module, paper, chapter, or referee report) against its manifest without rewriting it. Runs a deterministic gate for build, citations, numbers, facts, and leaks and stops on failure, then runs a finder over each section and a strong-model pass over the whole work, and adjudicates into checks/<date>/findings.json and report.md with anchored findings, severities, and honest NOT CHECKED coverage within a dollar budget. Use when asked to lint or review the whole talk, module, or paper, for a pre-ship review, or for the night shift. Revision stays serial and author-led.
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。
Turns raw captures (dictated braindumps in a deliverable's inbox/, or recent macwhspr dictation-log entries) into proposed planning-wiki changes, shown as one unified diff. Classifies each statement as a decision, evidence claim, question, task, or dropped item, traces it to its capture paragraph, tags unconfirmed names, numbers, and citations UNRESOLVED, and writes decisions only with the author's assent. Edits only the planning wiki, never source files. Use when asked to intake, absorb notes, or process the inbox, or after dictating notes from a talk, meeting, or reading session.
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。
End-of-session closure for a research or code repository. Records what changed into the project's own handoff and log files, separating verified work from work merely attempted, and reports what is left uncommitted. Use when wrapping up a session so the next one can resume without re-deriving state. Its start-of-session twin is sitrep.
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。
Interviews a researcher in rounds until an idea, design, or draft has no unexamined decision — numbered questions, each with why it matters and a recommended answer, facts looked up rather than asked, and settled decisions written to a file. Stages are idea (topic or hunch to a falsifiable question and contribution claim), design (estimand, identification, sample and power, measurement, analysis plan, pre-registration, venue), and defend (reviewer objections to a finished design or draft). Use when the user says "grill me", asks to stress-test or poke holes in an idea, design, or plan, asks what they are assuming, or brings an idea that is not yet a design. --plan grills software or process plans.
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。
Use when the primary outcome is creating publishable source-attributed content from URLs or supplied material, including research summaries, articles, briefs, and posts whose factual claims and quotations need reader-visible, verifiable citations.
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。
Illustrative Claude Code skill configuration. Use when learning the basic SKILL.md shape; follow the canonical runtime reference for the current field inventory.
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。
Research a specific technology, library, system, protocol, or tool to answer a concrete technical question with source-traceable evidence. Use when current implementation details, version behavior, configuration, compatibility, or authoritative technical facts must be verified rather than recalled. Also use when explicitly asked to incorporate verified findings into an existing skill.
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。
Sync a skill's content against the upstream library it covers — check whether the API descriptions, version references, and SOURCE: citations inside SKILL.md and its reference files still reflect what the library actually does today. Use when a library has released updates that may have changed the APIs the skill covers, when a skill references an old library version, when asked to sync, refresh, update, or check a skill against upstream docs, when the skill's content may have drifted from current library behavior, or when SOURCE: citations are stale. Accepts a SKILL.md path, skill directory, or plugin directory.
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。
Autonomous feature research and gap analysis. Use when starting /add-new-feature or analyzing existing architecture documents. Explores codebase patterns, identifies ambiguities, and produces feature-context-{slug}.md for orchestrator RT-ICA phase. Does NOT make technical decisions.
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。
Synthesis step in the multi-angle technical research pipeline. Receives structured outputs from all four research angles (api-state, ecosystem-research, impact-measurement, codebase-auditor), applies cross-angle signal weighting and conflict resolution, and produces a single synthesized Research section. Invoked by the technical-researcher orchestrator after all angle skills complete. Returns content to the orchestrator — does not write to the backlog.
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。
Research community usage patterns, real-world gotchas, and client compatibility for a specific known library, tool, or protocol feature. Use when a technical-researcher orchestrator needs community-sourced evidence about a named library or feature — bug reports, workarounds, compatibility gaps, and patterns from issue trackers and discussions. Distinct from the broad ecosystem-researcher agent — this skill targets a KNOWN entity and mines what real users have actually experienced, not what exists in a domain.
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。
Register a plan artifact via the MCP backlog server. Use when you produce a document or report that downstream agents or worktree-isolated environments need to retrieve — feature-context, codebase-analysis, architect, T0-baseline, TN-verification, or research artifacts. Triggers include "store an artifact", "register a plan artifact", "write a report to the backlog", "upload artifact content".
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。
Quantitative cost measurement for technical research — token injection costs, payload sizes, context window consumption, and file-level counts from actual repo files. Use when a technical-researcher orchestrator needs the cost dimension of adding or changing something: how many tokens will it inject, how big are the artifacts, what is the context window impact? This is NOT blast-radius analysis (which files break) — it covers size, tokens, and performance cost only.
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。
Bulk-refresh research entries in ./research/ using parallel research-curator agents. Use when /refresh-research is invoked, stale research needs updating, or bulk re-verification of research entries is requested. Inventories entries by review date and age, runs RT-ICA pre-flight, spawns agents in waves of 5, then validates, reviews, and commits through research-curator. Supports --all, --stale, --category, --layer, and --dry-run flags.
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。
Builds comprehensive Claude Code skills using parallel research agents — categorization, parallel documentation gathering, anti-hallucination checkpoints, and final validation. Use when building a skill from official docs, when "research for skill" or "create comprehensive skill" is requested, or when extensive multi-source documentation gathering is needed before skill creation.
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。
Orchestrate research entry lifecycle in ./research/ — create, batch-import, refresh stale entries, and validate structure. Use when asked to add a tool, research a URL, document a library, refresh research, validate entries, or given any tool or library URL. Supports --batch (parallel multi-URL), --rerun (refresh one or all entries), and --validate (structural check with auto-fix of error-severity issues).
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。
Manages the research/ knowledge base of verified tool and library research entries via knowledge-explorer.py. Commands — list (browse by category or SDLC layer), fetch-github (draft entry from GitHub repo), add (validate and route to category dir), update-append (append dated revision), generate-descriptions (repair missing or low-quality descriptions), migrate (convert inline-header entries to frontmatter). Use when browsing KB topics, adding or updating research entries, fetching GitHub repo metadata, generating descriptions in parallel via Haiku subagents, or migrating old-format entries to skill-spec frontmatter.
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。
Checks whether each claim in a manuscript is supported by the source it cites, reading the project's per-source Markdown knowledge base. Flags contradicted, unsupported, overclaimed, out-of-scope, and misattributed claims with verbatim source quotes. Runs citation-check first, and stops at a pre-flight gate when the knowledge base is missing, incomplete, or holds unconverted PDFs. Use to verify that a draft's claims match the sources it cites.
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。
Typesets a working paper or journal submission in house-style LaTeX from Markdown, Word (.docx), TeX, ODT, RTF, or HTML. Converts with pandoc, wraps the body in an EB Garamond template, builds the PDF with latexmk, and sets journal-specific spacing, page limits, anonymization, disclosures, and citation style. Use to format or convert a paper to LaTeX, make a working paper, or prepare a submission to a named journal.
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。