Browse Skills
18175 skills found
ln-170-code-comments-auditor.md
13
1
export
ln-170-code-comments-auditor
2
from
"levnikolaevich/claude-code-skills"
from
"levnikolaevich/claude-code-skills"
3
Audit code comments and docstrings quality across 6 categories (WHY-not-WHAT, Density, Forbidden Content, Docstrings, Actuality, Legacy). Use when code needs comment review, after major refactoring, or as part of ln-100-documents-pipeline. Outputs Compliance Score X/10 per category + Findings + Recommended Actions.
2026-01-21
rspec-coder.md
13
1
export
rspec-coder
2
from
"majesticlabs-dev/majestic-marketplace"
from
"majesticlabs-dev/majestic-marketplace"
3
This skill guides writing comprehensive RSpec tests for Ruby and Rails applications. Use when creating spec files, writing test cases, or testing new features. Covers RSpec syntax, describe/context organization, subject/let patterns, fixtures, mocking with allow/expect, and shoulda matchers.
2026-01-22
letta-agent-designer.md
13
1
export
letta-agent-designer
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guide for designing effective Letta agents. This skill should be used when users need help choosing agent architectures, designing memory blocks, selecting models, or planning tool configurations for their Letta agents.
2026-01-21
path-tracing.md
13
1
export
path-tracing
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for implementing path tracers and ray tracers to reconstruct or generate images. This skill applies when tasks involve writing C/C++ ray tracing code, reconstructing images from reference images, or building rendering systems with spheres, shadows, and procedural textures. Use for image reconstruction tasks requiring similarity matching.
2026-01-21
modernize-scientific-stack.md
13
1
export
modernize-scientific-stack
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guide for modernizing legacy Python 2 scientific computing code to Python 3 with modern libraries. This skill should be used when migrating scientific scripts involving data processing, numerical computation, or analysis from Python 2 to Python 3, or when updating deprecated scientific computing patterns to modern equivalents (pandas, numpy, pathlib).
2026-01-21
mteb-leaderboard.md
13
1
export
mteb-leaderboard
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
This skill provides guidance for retrieving and verifying information from dynamic ML leaderboards (MTEB, Scandinavian Embedding Benchmark, HuggingFace leaderboards, etc.) with specific temporal requirements. It should be used when tasks involve finding top-performing models, rankings, or benchmark results as of a specific date, especially when the data source is frequently updated.
2026-01-21
power-words.md
13
1
export
power-words
2
from
"majesticlabs-dev/majestic-marketplace"
from
"majesticlabs-dev/majestic-marketplace"
3
Enhance copy with emotional trigger words from 21 psychological categories. Transform bland text into compelling, conversion-focused content.
2026-01-22
build-pov-ray.md
13
1
export
build-pov-ray
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for building POV-Ray (Persistence of Vision Raytracer) from source, particularly legacy versions like 2.2. This skill should be used when tasked with downloading, compiling, and installing POV-Ray from source archives. It covers handling legacy C code, compressed archive formats, build system navigation, and verification strategies for successful compilation.
2026-01-21
db-wal-recovery.md
13
1
export
db-wal-recovery
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for recovering data from SQLite Write-Ahead Log (WAL) files that may be corrupted, encrypted, or inaccessible. This skill should be used when tasks involve database recovery, WAL file analysis, decrypting database files, or recovering missing/corrupted SQLite data. Helps avoid common pitfalls like fabricating data based on patterns instead of actual recovery.
2026-01-21
ln-160-docs-auditor.md
13
1
export
ln-160-docs-auditor
2
from
"levnikolaevich/claude-code-skills"
from
"levnikolaevich/claude-code-skills"
3
Audit project documentation quality across 6 categories (Hierarchy, SSOT, Compactness, Requirements, Actuality, Legacy). Use when documentation needs quality review, after major doc updates, or as part of ln-100-documents-pipeline. Outputs Compliance Score X/10 per category + Findings + Recommended Actions.
2026-01-21
win-back.md
13
1
export
win-back
2
from
"majesticlabs-dev/majestic-marketplace"
from
"majesticlabs-dev/majestic-marketplace"
3
Design win-back campaigns to re-engage dormant customers and recover churned users with targeted messaging, special offers, and feedback collection to understand and address churn reasons.
2026-01-22
gpt2-codegolf.md
13
1
export
gpt2-codegolf
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for implementing neural network inference (like GPT-2) under extreme code size constraints. This skill should be used when tasks require implementing ML model inference in minimal code (code golf), parsing model checkpoints in constrained environments, or building transformer architectures in low-level languages like C with strict size limits.
2026-01-21
docx.md
13
1
export
docx
2
from
"lawvable/awesome-legal-skills"
from
"lawvable/awesome-legal-skills"
3
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks
2026-01-21
winning-avg-corewars.md
13
1
export
winning-avg-corewars
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for developing CoreWars warriors that achieve target win rates against specific opponents. This skill should be used when tasks involve writing, optimizing, or debugging Redcode assembly warriors for the CoreWars programming game, particularly when win rate thresholds must be met against multiple opponents.
2026-01-21
fix-code-vulnerability.md
13
1
export
fix-code-vulnerability
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for identifying and fixing security vulnerabilities in code. This skill should be used when tasks involve fixing CWE-classified vulnerabilities, addressing security flaws, patching injection vulnerabilities, or responding to security-related test failures.
2026-01-21
financial-document-processor.md
13
1
export
financial-document-processor
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for processing financial documents (invoices, receipts, statements) with OCR and text extraction. This skill should be used when tasks involve extracting data from financial PDFs or images, generating summaries (CSV/JSON), or moving/organizing processed documents. Emphasizes data safety practices to prevent catastrophic data loss.
2026-01-21
adaptive-rejection-sampler.md
13
1
export
adaptive-rejection-sampler
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for implementing adaptive rejection sampling (ARS) algorithms for generating random samples from log-concave probability distributions. This skill should be used when tasks involve implementing ARS, rejection sampling, or Monte Carlo methods that require sampling from custom probability distributions, particularly in R or other statistical computing languages.
2026-01-21
schemelike-metacircular-eval.md
13
1
export
schemelike-metacircular-eval
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guide for building metacircular evaluators in Scheme-like languages. This skill applies when implementing interpreters that can interpret themselves, handling tasks involving eval/apply loops, environment management, closure implementation, and multi-level interpretation. Use for any metacircular evaluator, Scheme interpreter, or self-interpreting language implementation task.
2026-01-21
AILANG Sprint Planner.md
13
1
export
AILANG Sprint Planner
2
from
"sunholo-data/ailang"
from
"sunholo-data/ailang"
3
Analyze design docs, calculate velocity from recent work, and create realistic sprint plans with day-by-day breakdowns. Use when user asks to "plan sprint", "create sprint plan", or wants to estimate development timeline.
2026-01-21
torch-pipeline-parallelism.md
13
1
export
torch-pipeline-parallelism
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for implementing PyTorch pipeline parallelism for distributed model training. This skill should be used when tasks involve implementing pipeline parallelism, distributed training with model partitioning across GPUs/ranks, AFAB (All-Forward-All-Backward) scheduling, or inter-rank tensor communication using torch.distributed.
2026-01-21
gcode-to-text.md
13
1
export
gcode-to-text
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Decode and interpret text content from G-code files by analyzing toolpath geometry and coordinate patterns. This skill should be used when extracting text, letters, or symbols that are encoded as movement commands in G-code files (e.g., 3D printing, CNC engraving, laser cutting). Applies to tasks like identifying what text a G-code file will print/engrave, reverse-engineering embossed or engraved text from toolpaths, or visualizing G-code geometry to reveal hidden content.
2026-01-21
polyglot-rust-c.md
13
1
export
polyglot-rust-c
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for creating polyglot source files that compile and run correctly as both Rust and C/C++ programs. This skill should be used when asked to create code that is valid in multiple programming languages simultaneously, particularly Rust and C/C++ polyglots.
2026-01-21
digitalocean-coder.md
13
1
export
digitalocean-coder
2
from
"majesticlabs-dev/majestic-marketplace"
from
"majesticlabs-dev/majestic-marketplace"
3
This skill guides writing DigitalOcean infrastructure with OpenTofu/Terraform. Use when provisioning Droplets, VPCs, Managed Databases, Firewalls, or other DO resources.
2026-01-22
llm-inference-batching-scheduler.md
13
1
export
llm-inference-batching-scheduler
2
from
"letta-ai/skills"
from
"letta-ai/skills"
3
Guidance for implementing batching schedulers for LLM inference systems with compilation-based accelerators. This skill applies when optimizing request batching to minimize cost while meeting latency thresholds, particularly when dealing with shape compilation costs, padding overhead, and multi-bucket request distributions. Use this skill for tasks involving batch planning, shape selection, generation-length bucketing, and cost-model-driven optimization for neural network inference.
2026-01-21