template

Skill for the core infrastructure module providing logging, configuration, exception handling, progress tracking, checkpoints, retry logic, pipeline execution, performance monitoring, security, file operations, and multi-project orchestration. Use when setting up logging, loading config, handling errors, running pipelines, or monitoring performance.

Skill for the documentation infrastructure module providing figure management, image handling, markdown integration, and API glossary generation. Use when managing research figures, inserting images into manuscripts, auto-numbering figures, or generating API documentation.

Skill for the LLM infrastructure module providing local Large Language Model integration via Ollama. Covers client initialization, prompt templates, output validation, manuscript review generation, conversation context, and CLI usage. Use when querying LLMs, generating manuscript reviews, validating LLM outputs, or managing Ollama models.

Python CLI and menu orchestration for pipeline runs — project slug validation, interactive picker, PipelineRunner wrapping PipelineExecutor, per-stage logs, secure pipeline wrapper. Use when extending run.sh behavior, fixing menu/CLI routing, or testing discovery helpers.

Skill for the project management infrastructure module providing multi-project discovery, structure validation, and metadata extraction. Use when discovering active projects, validating project directory structure, or extracting project configuration metadata.

Skill for the publishing infrastructure module providing academic publishing workflows including BibTeX CLI citation generation, APA/MLA citation helper functions, DOI management, Zenodo publication, arXiv submission preparation, GitHub releases, PyPI and TestPyPI package distribution, static-site deployment to GitHub Pages / Cloudflare Pages / Netlify, multi-target long-horizon archival (IPFS Pinata, Web3.Storage, Software Heritage), a central platform registry, and publication readiness validation. Use when publishing research, generating citations, minting DOIs, distributing Python packages, deploying documentation sites, or preparing archival submissions.

Skill for the rendering infrastructure module providing multi-format output generation including PDF manuscripts, HTML web pages, and Beamer/Reveal.js slides. Use when rendering research outputs, converting markdown to PDF, generating slides, or configuring LaTeX rendering.

Skill for the reporting infrastructure module providing pipeline reporting, error aggregation, executive summaries, dashboard generation, test reporting, and multi-project reports. Use when generating build reports, aggregating errors, creating visual dashboards, or producing executive summaries across projects.

Discovery utilities. Hosts three subpackages — `literature` for Paperclip-style multi-source academic search across arXiv, Crossref, local JSON corpora, and (opt-in) the Paperclip API, with deterministic JSON caching, a `LiteratureClient` aggregator, normalised `Paper` records, and a CLI; `exa` for Exa-backed general web search, content extraction, grounded answers, and find-similar via `ExaClient` (search/contents/answer/find_similar) and a CLI; and `deep_research` for provider-neutral long-running deep research over OpenAI (`o3-deep-research`) and Gemini, packaging a project's manuscript/outputs into the prompt and saving full reports with citations (PAID — ≈$2/report OpenAI, ≈$25 Gemini; see its README cost model). Use when the user wants to find papers, build reading lists, populate references.bib from a query, replay a prior search reproducibly, run general web search / content extraction / grounded answers, or dispatch a manuscript for a deep-research review with new citations and fix suggestions. Desig

Skill for the Self-Improvement Agent (SIA) harness contract. Use when validating task public/private layouts, generation artifact trees, evaluation runners, fixture replay loops, or opt-in live Meta→Target→Feedback cycles in template projects.

Top-level skill for the research template infrastructure layer. Use in Cursor, Claude Code, or similar agents when editing or importing anything under infrastructure/, understanding the two-layer architecture, or wiring build/validation/rendering/publishing. Covers module discovery, import patterns, thin orchestrators, per-subpackage SKILL.md paths, and .cursor/skill_manifest.json (see infrastructure.skills).

Skill for the steganography infrastructure module providing QR code generation with dynamic mailto links, hash manifests, metadata payloads, and document-wide overlay processing. Use this module to insert opt-in cryptographic and steganographic provenance data onto PDFs.

Use when auditing public research exemplars for deterministic publication readiness across tests, methods, evidence, artifacts, figures, manuscript sources, and generated outputs.

Skill for the validation infrastructure module providing PDF validation, markdown validation, output integrity checks, link verification, documentation audits, issue categorization, and repository scanning. Use when validating research outputs, checking document quality, running audits, or verifying cross-references.

Multi-phase literature-review exemplar with phase-aware retrieval, filtering, provenance, and cross-phase validation.

Phase-aware tooling for injecting advanced-review evidence and statistics into Markdown manuscript templates.

Core inference logic, prompt construction, and RDF/Nanopublication serialization.

Operations for federated API querying across ten literature engines (arXiv, Semantic Scholar, OpenAlex, Crossref, PubMed, SovietRxiv, ChinaRxiv, Europe PMC, bioRxiv, medRxiv).

Tooling for injecting JSON/CSV statistics into Markdown evaluation templates.

Core orchestration guidelines and MCP interactions for the src/ library.

Orchestrates matplotlib and seaborn pipelines for rendering figures.

Publishing scripts for DOI-bearing project releases, optional mirror uploads, PyPI release validation, post-publish verification, and publication export. Use with docs/guides/publication-runbook.md for standalone GitHub + Zenodo release workflows.

Pipeline execution runners for the template research framework. Contains execute_pipeline.py (single-project), execute_multi_project.py (multi-project serial/parallel), and run_matrix.py (deterministic matrix).

Operations for phase-aware federated retrieval across ten literature engines, preserving provenance from broad discovery through focused synthesis.

End-to-end publication-readiness audit for public template exemplars — tests, no-mocks, methods contracts, claims, evidence, figures, references, rendered outputs, and deterministic regeneration. USE WHEN preparing a template or project for release, DOI deposit, peer review, or a publication sign-off.

Router and workflow hub for the Research Project Template — code, tests, manuscripts, pipeline, validation, docs, and reproducibility. USE WHEN the user wants to audit the repo, debug ./run.sh or execute_pipeline.py, add a feature, write tests, scaffold a manuscript, verify claims, fix cross-references, run validation gates, refactor, or prepare a Zenodo release, discover relevant template skills, improve agent routing, review external agentic operating models or retrieval references such as Steward OS, AutoResearch CLI, or LEANN, research a topic, write/review/revise a paper, or run a research-to-publication workflow — even if they never say "prompt", "skill", or docs/prompts. Also USE WHEN intent is ambiguous ("something wrong with my manuscript", "full health check", "fix the pipeline") — pick ONE child skill from the routing table and follow it. Do NOT use for generic homework, unrelated app security scans, or casual PDF summarization.

Methods orchestration contract builder for template projects. Use when mapping pipeline stages, manuscript methods, artifact manifests, evidence registries, and validation commands into one reproducible methods plan.

Deterministic benchmark harnesses for public template exemplars. Use when scoring generated project outputs against benchmark manifests, refreshing the default template smoke manifest, checking publication-readiness rubrics, or adding bounded no-network readiness checks for public template outputs.

Content-addressed provenance DAG for research lineage tracking. Use for: recording which pipeline stage produced which artifact, querying edges between recorded nodes, running a DAG-wide review pass. CLI: python -m infrastructure.provenance {list,record-artifact,review}. Library: infrastructure.provenance.Provenance (record/link/get/list/query). Orchestrator: scripts/pipeline/stage_09_provenance_record.py --project {name} --stage NAME

Programmatic discovery of agent SKILL.md files under configured public repo roots (infrastructure, scripts, projects/templates, resource-pool templates, docs/prompts, .agents/skills, and .cursor/skills). Use when enumerating skills, validating .cursor/skill_manifest.json, writing docs/_generated/skills_index.md, checking docs/prompts workflow contracts, or wiring editor/Codex/Hermes/MCP automation. Exposes discover_skills, write_skill_manifest, manifest_matches_discovery, and check_skill_contracts.

LLM-based extraction of per-paper workflow graphs and content/structural reproducibility scoring.

Audit and quality-gate scripts for the template research framework. Covers documentation linting, filepath audits, mock-usage checking, template drift, and confidentiality / git-guard checks.

Numbered pipeline stage orchestrators (stages 00–12) for the template research framework. Each stage_NN_*.py is a thin orchestrator that wires the repo root onto sys.path and delegates to infrastructure/ modules.

Shell helper scripts for the template research framework. Covers system health checks, local CI reproduction, uv bootstrap, and rsync backup tiers. Scripts live at scripts/ root level.

Optional validation gates for Hermes-plugin and advisory workflows. Includes cache validation, methods plan checks, line-count gates, security scanning, plugin export checks, and skill reachability checks. None run in the default pipeline; invoked explicitly when needed.

Search 8+ scientific databases through a uniform Connector interface. Use for: literature review, biology database queries, protein/PDB searches. CLI: python -m infrastructure.search.connectors {list-dbs,search}. Config: set queries in projects/{name}/manuscript/config.yaml `connector_search:` block. Orchestrator: scripts/pipeline/stage_08_connector_search.py --project {name}

Paperclip-style multi-source literature search across arXiv, Crossref, local JSON corpora, and (opt-in) the Paperclip API. Provides Paper/SearchQuery/SearchResult data models, a LiteratureClient aggregator with per-backend failure isolation, DOI/arXiv-aware deduplication via merge_papers, deterministic JSON caching via SearchCache, an HttpClient protocol for test injection, and a CLI (search/to-bibtex). Use when finding papers by topic, building reading lists, populating references.bib from a query, or replaying a prior search reproducibly.

Orchestration for bibliometrics, topological network analysis, and hypothesis scoring.

Prose-review pipeline exemplar — readability gates, structural checking, BibTeX validation, and quality review workflows.

Derived documentation generators for the template research framework. Scripts that write to docs/_generated/ and update in-place doc blocks. Currently at scripts/ root; this directory is the planned migration target.