Cross-agent Agent Skills library with a Hermes-native retrieval plugin · Mixed: 21 skills are labeled Stable and eight Beta, based on the README inventory.

moonlight-lupin/agent-skills

MIT-licensed collection of 29 self-contained Agent Skills built for Hermes Agent, plus a Hermes-only BM25 skill-retrieval plugin; Claude Code can install the SKILL.md packages, but workflows may require mapping Hermes tool names and the plugin itself is explicitly incompatible with Claude Code.

Research and fact-checkingCreative media generationProductivity and document automationAgent operationsMLOps and model evaluationWeb scrapingDevOpsRetrieval-augmented generationCompliance-support research
Routing score
80.0
Readiness
Usable for Claude Code with adaptation; individual dependencies, credentials, and host-tool mappings vary by skill.
License
MIT
Maintenance
active
Components
20
Revision
0

Selection

Select when

  • You want portable SKILL.md workflows that Claude Code can load from .claude/skills.
  • You need source-grounded research, fact-checking, citation, or monitoring procedures.
  • You want bundled local scripts for RAG, documents, enrichment, media, or operations.
  • You prefer installing only selected skills from a broad catalog.
  • You already use Hermes Agent and want its native tool architecture.
  • You need EPUB or PDF ingestion into a cited semantic-search library.
  • You want dry-run, confirmation, or evidence-label disciplines embedded in workflows.
  • You are prepared to inspect dependencies and map Hermes-specific tools to Claude Code.

Boundaries

Avoid when

  • You need the included BM25 retrieval plugin to run inside Claude Code.
  • You require every skill to work without modifying Hermes-specific tool references.
  • You cannot permit external API calls for skills that depend on fal.ai, PDL, Pexels, NVIDIA, or OpenRouter.
  • You need a dependency-free collection across all capabilities.
  • You require all components to be repository-labeled Stable.
  • You need independent validation of production quality, security, or model-output accuracy.
  • You require fully local processing for enrichment, media generation, or hosted embeddings.
  • You want a narrowly scoped software-engineering-only skill set.

Strengths

Capabilities

Provides 29 README-enumerated skills across seven top-level domains.Uses self-contained SKILL.md folders with optional scripts, references, examples, tests, and eval fixtures.Installs all or selected skills through the documented Skills CLI flow.Supports Claude-targeted installation into .claude/skills through the documented GitHub CLI flow.Documents manual copying into user-level agent skill directories.Uses a hash-pinned skills-lock.json in the stated whole-catalog installation path.Covers deep research with source ranking, refutation polarity, and explicit evidence-basis labels.Covers entity dossiers, public sanctions-list signals, fact checking, media analysis, and citation tracking.Builds a sqlite-vec semantic library using NVIDIA or legacy OpenRouter embeddings.Supports EPUB and PDF conversion, incremental indexing, per-chunk citations, and optional MCP access in library-rag.Provides website reconnaissance and browser-oriented extraction guidance with JSONL output conventions.Provides staged fal.ai image and video workflows with dry-run and cost-awareness controls.Provides Pexels stock-photo search with attribution guidance.Provides local Word and Excel mail merge with explicit missing-value handling.Provides travel, decision-log, scheduled-summary, file-organization, conversion, and task-brief workflows.Provides blind model comparison and embedding benchmarking guidance.Provides skill maintenance, Claude-plugin-to-Hermes conversion, log analysis, token auditing, and Hermes onboarding.Ships a Hermes-only BM25 plugin that injects top-ranked skills instead of the full catalog.States Agent Skills specification validation and repository CI covering pytest suites and routing fixtures.Labels per-skill maturity, test style, dependencies, platform caveats, and credential requirements in the root README.

Risk profile

Risks and limitations

  • Uncertainty: only selected first-party files were supplied, so most SKILL.md files, scripts, tests, evals, manifests, CI workflows, and dependency files were not inspected.
  • Uncertainty: repository metadata is dated in 2026 relative to this analysis context, so activity, adoption, and recency cannot be independently reconciled.
  • Uncertainty: repository labels such as Stable, production-tested, self-contained, and tested were not independently reproduced.
  • The skill-retrieval plugin is explicitly Hermes-only and incompatible with Claude Code.
  • Claude Code must map Hermes-specific tools such as web_search, web_extract, delegate_task, and cronjob where host conventions differ.
  • No minimum Claude Code version, Claude compatibility matrix, or supplied Claude integration test was evidenced.
  • Some tests are routing or output-contract fixtures and explicitly do not execute live models in CI.
  • Skills can require third-party APIs, paid usage, credentials, network access, Python packages, curl, pandoc, browser tooling, or SQLite extension loading.
  • Research, sanctions signals, media analysis, scraping, and generated outputs still require qualified human review and lawful use.
  • Hosted embedding, enrichment, media, search, and stock-photo services receive submitted queries or content under their own policies.
  • The library-rag files disagree with the root badge on Python requirements, stating Python 3.9+ versus repository-level Python 3.11+.
  • No independent security audit, privacy assessment, comprehensive threat model, or cross-host quality benchmark was supplied.

The repository documents dry runs, confirmation gates, credential separation, local-only modes, sanctions-screening boundaries, and a nonpersistent Hermes retrieval patch. However, bundled scripts can read and write files, fetch websites, call third-party APIs, load SQLite extensions, move files, schedule work, or probe endpoints. Implementations were not fully supplied, so users should inspect each selected skill and dependency, scope credentials, review proposed filesystem changes, and preserve host approvals and sandboxing.

Component inventory

20 documented components

skill

image-studio

Staged fal.ai image creation, editing, upscaling, background removal, and photo cleanup with cost tracking.

creative/image-studio/SKILL.md
skill

clips-studio

Staged fal.ai video workflow for text-to-video, still-image animation, and camera moves.

creative/clips-studio/SKILL.md
skill

pexels-stock-photos

Searches and downloads real stock photos through the Pexels API with attribution handling.

creative/pexels-stock-photos/SKILL.md
skill

deep-research

Iterative, source-grounded research with source ranking, refutation checks, structured evidence, and labeled claims.

research/deep-research/SKILL.md
skill

entity-research

Builds cited company or person dossiers covering identity, ownership, adverse media, litigation, and sanctions signals.

research/entity-research/SKILL.md
skill

news-monitoring

Produces recurring, deduplicated, multilingual news digests with cron delivery.

research/news-monitoring/SKILL.md
skill

notebooklm-mode

Answers questions from a source vault using strict or augmented source grounding.

research/notebooklm-mode/SKILL.md
skill

people-enrichment

Uses People Data Labs to enrich or search people and companies and export styled Excel workbooks.

research/people-enrichment/SKILL.md
skill and MCP service

library-rag

Converts EPUB/PDF content, builds a Nemotron/sqlite-vec semantic index, and returns cited library search results.

research/library-rag/SKILL.md
skill

source-tracker

Maintains a persistent citation database with URL deduplication, topic tags, health checks, and bibliography export.

research/source-tracker/SKILL.md
skill

fact-checker

Verifies targeted claims and returns cited reports with confidence ratings.

research/fact-checker/SKILL.md
skill

media-analyzer

Analyzes rhetoric such as loaded language, framing, and omission without assigning political labels.

research/media-analyzer/SKILL.md
skill

endpoint-probe

Discovers and interprets API or MCP surfaces across REST, GraphQL, SOAP, and JSON-RPC.

research/endpoint-probe/SKILL.md
skill

youtube-topic-research

Searches YouTube, retrieves transcripts, and summarizes material around a topic.

research/youtube-topic-research/SKILL.md
skill

model-compare

Runs blind multi-model A/B comparisons in simple, tool, coding, review, and embedding-benchmark modes.

mlops/model-compare/SKILL.md
skill

website-scraping

Seven-step web extraction playbook covering reconnaissance, tool selection, anti-bot handling, and JSONL output.

web-scraping/website-scraping/SKILL.md
skill module

Productivity skills

Seven skills for template filling, travel itineraries, decision logs, format conversion, scheduled summaries, file organization, and task briefs.

productivity/
skill module

Agent operations skills

Five skills for Claude-plugin conversion, skill-library maintenance, log analysis, token-overhead audits, and Hermes onboarding.

agent-ops/
skill

disk-cleanup

Surveys disk usage, separates safe and approval-required cleanup actions, executes approved work, and verifies reclaimed space.

devops/disk-cleanup/SKILL.md
Hermes plugin

skill-retrieval

Replaces Hermes's full skill list with BM25 top-K retrieval and injects relevant skill descriptions per turn.

plugins/skill-retrieval/

Technical profile

Requirements and configuration

License
MIT according to repository metadata and supplied first-party files.
Repository Language
GitHub metadata identifies Python as the primary language.
Inventory
The root README enumerates 29 skills and one Hermes Agent plugin.
Skill Format
Agent Skills SKILL.md folders with metadata and optional scripts, references, examples, tests, and evals.
Claude Installation
Documented paths include Skills CLI installation, Claude-targeted gh skill installation, and copying into ~/.claude/skills/.
Hermes Plugin
skill-retrieval uses BM25 through a Python register() hook and plugin.yaml, developed against Hermes Agent >=0.20.0.
Runtime
Repository badge states Python 3.11+, while individual skills commonly state Python 3.8+ and library-rag states Python 3.9+.
Testing
The README reports pytest suites and routing/output fixtures, with live-model execution excluded from fixture CI.
Rag Stack
library-rag uses sqlite-vec plus NVIDIA Nemotron-3-Embed-1B by default and supports a legacy OpenRouter bge-m3 path.
External Services
Documented integrations include fal.ai, Pexels, People Data Labs, NVIDIA NIM, OpenRouter, public sanctions lists, and host web tools.
Artifacts
Outputs include cited reports, JSONL, Markdown, XLSX, DOCX-derived files, ICS, images, videos, SQLite indexes, and bibliographies.
Plugin Scope
The included retrieval plugin extends Hermes prompt assembly, not Claude Code.

Classification

How it enters the stack

Context InjectionTool SurfaceSkill Authoring

Evidence: Claude Code can load the SKILL.md packages from .claude/skills, and many skills include executable helper scripts. Evidence: skill-maintainer covers authoring and curation. The BM25 plugin is Hermes-only; medium effort reflects tool-name adaptation and per-skill dependencies.

Claude Extension · medium setup effort · high confidence · automated

Evidence and risk

Primary sources

first_party_fileREADME.mdhttps://github.com/moonlight-lupin/agent-skills/blob/main/README.md

Routing context

Conflicts, complements, and synergies

overlaps

gh_d4vinci_scrapling

Both provide Claude-loadable scraping guidance, but Scrapling supplies the underlying framework and MCP server while moonlight-lupin provides a broader multi-skill collection.

medium confidence
extends

gh_nousresearch_hermes_agent

The skills target Hermes Agent's tool architecture, and the included BM25 plugin installs into and hooks the Hermes runtime.

high confidence
overlaps_with

gh_orchestra_research_ai_research_skills

Both provide MIT-licensed, installable research-oriented Agent Skills for Claude Code, but this repository is Hermes-first and broader in productivity and creative operations.

medium confidence