template-deep-research
Template-native research intake, literature search, source verification, synthesis, fact-checking, and systematic-review planning. USE WHEN the user asks to research a topic, build a literature corpus, fact-check claims, prepare a PRISMA-style review, or clarify a research question before manuscript work.
Best use case
template-deep-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Template-native research intake, literature search, source verification, synthesis, fact-checking, and systematic-review planning. USE WHEN the user asks to research a topic, build a literature corpus, fact-check claims, prepare a PRISMA-style review, or clarify a research question before manuscript work.
Teams using template-deep-research should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/deep-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How template-deep-research Compares
| Feature / Agent | template-deep-research | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Template-native research intake, literature search, source verification, synthesis, fact-checking, and systematic-review planning. USE WHEN the user asks to research a topic, build a literature corpus, fact-check claims, prepare a PRISMA-style review, or clarify a research question before manuscript work.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Deep research Template-native research workflow. This skill routes to existing repository systems instead of running an autonomous external agent suite. ## Natural invoke - "Research this topic and build the source corpus" - "Do a literature review with citation keys" - "Fact-check these manuscript claims" - "Guide me from vague research interest to answerable question" - "Plan a systematic review with inclusion and exclusion criteria" ## Inputs to confirm - **Research goal** - question, audience, and expected deliverable. - **Mode** - full, quick, lit-review, fact-check, guided, or systematic-review. - **Corpus source** - arXiv, Crossref, local JSON corpus, provided papers, or project artifacts. - **Project target** - if results feed a manuscript, use `docs/_generated/active_projects.md`. ## Workflow 1. **Question framing** - turn vague topics into scoped research questions, explicit in/out boundaries, and search terms. Guided mode asks before converging. 2. **Source discovery** - use `infrastructure.search.literature` and project-local corpora; record query, backend, date, DOI/arXiv IDs, and failures. 3. **Source verification** - check DOI/arXiv metadata, citation keys, retraction or source-tier warnings where available; do not invent unavailable bibliographic fields. 4. **Synthesis** - hand off to [literature-synthesis](../literature-synthesis/SKILL.md) for per-paper notes, thematic clusters, contradictions, and gap analysis. 5. **Claim bridge** - when research supports manuscript prose, create citekey-linked notes that [manuscript-claim-verification](../manuscript-claim-verification/SKILL.md) can audit later. ## Deliverables - Research brief: question, scope, search strategy, corpus table, and evidence gaps. - Literature synthesis with bracket-key citations and source-tier notes. - Fact-check report: claim, source, verdict, uncertainty, action. - For systematic review mode: protocol draft, inclusion/exclusion criteria, screening counts, and limitations. ## Verification commands ```bash uv run python -m infrastructure.search.literature search "QUERY" --limit 20 uv run python -m infrastructure.reference.citation validate projects/<project>/manuscript/references.bib uv run python -m infrastructure.validation.cli evidence projects/<project> --fail-on-issues ``` ## References - [MODE_REGISTRY.md](../MODE_REGISTRY.md) - [literature-synthesis](../literature-synthesis/SKILL.md) - [manuscript-claim-verification](../manuscript-claim-verification/SKILL.md)
Related Skills
infrastructure-autoresearch
Skill for deterministic AutoResearch readiness planning. Use when adding, validating, or documenting opt-in autoresearch.yaml controls, stage-gate readiness, evidence-grounded claims, artifact readiness reports, or AutoResearchClaw-inspired workflow checks in template projects.
template-validation-quality
Run validation CLI, prerender, markdown/PDF/integrity gates, and QA workflows for the Research Project Template. USE WHEN validate manuscript, check PDF for ?? refs, prerender gate, link checker, output integrity, or pre-commit validation — even without validation_quality prompt.
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Create pytest suites under the no-mocks policy — real data, temp files, subprocess, pytest-httpserver. USE WHEN adding tests, raising coverage, testing new src/ module, or user forbids mocks.
template-reproducibility-audit
Deterministic reproducibility audit — fixed seeds, regenerate-from-clean, double-run diff before Zenodo/arXiv/release. USE WHEN outputs drift between runs, "worked on my machine", need regenerate-from-clean proof, or pre-release reproducibility check — even without naming docs/prompts.
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Repo-wide methods orchestration workflow for the Research Project Template. USE WHEN the user asks to add, audit, improve, or validate methods, methodology, method contracts, stage-to-method wiring, artifact/evidence provenance, or orchestration across template projects.
template-manuscript-cross-references
Audit or author registry-driven manuscript cross-refs — labels.yaml, [[FIG:]], [[THMREF:]], [[VAR:]] tokens. USE WHEN fixing figure/equation/theorem numbering, orphan registry keys, hard-coded "Theorem 7.3" in prose, or [[MISSING:]] injection failures — even for Pandoc projects that also use a YAML registry.
template-manuscript-creation
Scaffold a research manuscript and project layout from a research brief — sections, config.yaml, src/, scripts/, tests. USE WHEN starting a new paper, new projects/ tree, manuscript from topic description, or aligning with template_code_project exemplar — even without copy-paste prompts.
template-manuscript-claim-verification
Triple-pass verification of every manuscript claim against code, data, refs, and renderer; repair prose while staying renderable. USE WHEN pre-submission, pre-Zenodo, pre-arXiv, abstract numbers disagree with CSV, citations do not support sentences, or user asks to triple-check / verify every claim — even without docs/prompts. Not for casual PDF summary.
template-feature-addition
End-to-end feature work across src/, scripts/, tests/, manuscript, and docs for the Research Project Template. USE WHEN adding a pipeline-visible feature, new analysis stage, manuscript-facing output, or cross-layer integration — even without feature_addition prompt.
template-documentation-creation
Author or refresh AGENTS.md and README.md for template directories — accurate commands, Mermaid where helpful, link _generated/active_projects.md. USE WHEN folder needs AGENTS, README audit, doc contract fix, or signposting after code change — even without documentation_creation prompt.