Agent skill

Cafci

by gauss314 in gauss314/skills

Datos de fondos comunes de inversion argentinos via CAFCI (Camara Argentina de Fondos Comunes de Inversion).

MITAuto-check passedDocuments & Office

Install Cafci

skills CLI
$ npx skills add gauss314/skills --skill cafci -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install gauss314/skills cafci --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/gauss314/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cafci .claude/skills/cafci && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cafci
GitHub stars
248
Token cost
~2.9k tokens
SKILL.md length
827 words
Files
3 (incl. scripts, references)
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

Datos de fondos comunes de inversion argentinos via CAFCI (Camara Argentina de Fondos Comunes de Inversion).

  • Works in 4 steps: /consulta-de-fondos.json (catalogo… → /pb_get (XLSX diario) → defuddle.md/.../fondos/{F}?clase={C}… → …
  • Tasks that involve Excel spreadsheets
  • SKILL.md covers ⚠️ Aviso Legal, 📌 Importante: API REST…, Scripts and Uso rapido, plus 6 more sections
  • Runs Python scripts from its folder; calls pip and jq

What it does

Cafci is an agent skill from gauss314/skills. Datos de fondos comunes de inversion argentinos via CAFCI (Camara Argentina de Fondos Comunes de Inversion). Combina catalogo JSON (1152 fondos, 4615 clases, fees, IDs, metadata), snapshot diario XLSX (VCP, patrimonio, market share, variaciones), ficha individual markdown (rendimientos TNA por periodo) y composicion de cartera (top activos). Sin API key.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts and reference files (for example `references/REFERENCE.md` and `scripts/fetch_cafci.py`).

It sits in Documents & Office, covering Excel spreadsheets. It works with Microsoft Excel. The repository describes itself as: Financial market data consumption skills for claude code and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Excel spreadsheets

Example prompts

  • “Use the cafci skill to dato de fondos comunes de inversion argentinos via CAFCI (Camara Argentina de Fondos Comunes de Inversion)”
  • “/cafci”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. /consulta-de-fondos.json (catalogo completo)
  2. /pb_get (XLSX diario)
  3. defuddle.md/.../fondos/{F}?clase={C} (ficha markdown)
  4. .../fondos/{F}?clase={C} (HTML para composicion de cartera)

What it can do on your machine

Read from SKILL.md and the folder at commit 5156f81. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • pip
    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cafci loads about 2.9k tokens when it runs, and up to ~8.3k if it reads all its reference files. Until then it costs about 91 tokens; SKILL.md has 827 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from gauss314/skills at commit 5156f81, republished under its MIT licence (© gauss314). 827 words, ~2,930 tokens.

Download SKILL.mdSave it as .claude/skills/cafci/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
cafci
description
Datos de fondos comunes de inversion argentinos via CAFCI (Camara Argentina de Fondos Comunes de Inversion). Combina catalogo JSON (1152 fondos, 4615 clases, fees, IDs, metadata), snapshot diario XLSX (VCP, patrimonio, market share, variaciones), ficha individual markdown (rendimientos TNA por periodo) y composicion de cartera (top activos). Sin API key.
license
MIT

CAFCI — Fondos Comunes de Inversion Argentinos

Skill para consultar informacion publica de fondos comunes de inversion en Argentina via las 4 fuentes oficiales de CAFCI (Camara Argentina de Fondos Comunes de Inversion).

Cubre 1152 fondos y 4615 clases activas al 2026-06: Money Market, Renta Fija, Renta Variable, Renta Mixta, PyMes, Retorno Total, Infraestructura, Fondos Cerrados, ASG, RG900.


  • API publica sin documentacion oficial. Los endpoints pueden cambiar sin aviso (como paso con la API REST anterior, discontinuada en 2026-04).
  • Respetar terminos de uso del CAFCI.
  • Los datos son delayed (cierre del dia habil, ~18hs ART).
  • Para uso comercial intensivo, contactar al CAFCI para feeds oficiales.
  • Rendimientos pasados no garantizan rendimientos futuros.

📌 Importante: API REST anterior DISCONTINUADA

La API REST api.pub.cafci.org.ar/tipo-renta, /fondo/{id}, /estadisticas/... fue discontinuada en 2026-04 (HTTP 403 "Route not allowed"). El unico path que sigue activo en ese host es /pb_get.

Esta skill usa las 4 fuentes alternativas que la reemplazaron:

  1. /consulta-de-fondos.json (catalogo completo)
  2. /pb_get (XLSX diario)
  3. defuddle.md/.../fondos/{F}?clase={C} (ficha markdown)
  4. .../fondos/{F}?clase={C} (HTML para composicion de cartera)

Scripts

ScriptDescripcion
fetch_cafci.pyScript principal: todos los endpoints + funciones de consulta

Requiere: pip install openpyxl (para parsear el XLSX diario).


Uso rapido

bash
# ── DATASETS ENTEROS (con cache local diario) ──────────────────────────

# Catalogo completo: 1152 fondos, 4615 clases con IDs, honorarios, metadata
py scripts/fetch_cafci.py catalogo
py scripts/fetch_cafci.py catalogo -o catalogo.json    # guarda 2.7MB
py scripts/fetch_cafci.py catalogo --no-cache          # fuerza refetch

# Snapshot diario: VCP, patrimonio, variaciones (dia/mes/YTD/12m)
py scripts/fetch_cafci.py diario
py scripts/fetch_cafci.py diario -o diario.json
py scripts/fetch_cafci.py diario --no-cache

# ── CONSULTAS SOBRE EL CACHE ───────────────────────────────────────────

# Buscar fondo por nombre (parcial, case-insensitive)
py scripts/fetch_cafci.py buscar "ahorro"
py scripts/fetch_cafci.py buscar "delta"
py scripts/fetch_cafci.py buscar "renta fija"

# Resolver IDs (mas compacto: solo fondo_id, clase_id, nombres)
py scripts/fetch_cafci.py resolve "ieb estrategico"
py scripts/fetch_cafci.py resolve "1810"

# Top N por patrimonio en una categoria del diario
py scripts/fetch_cafci.py top "Mercado de Dinero Peso Argentina"
py scripts/fetch_cafci.py top "Mercado de Dinero Peso Argentina" --limit 20
py scripts/fetch_cafci.py top "Renta Variable Peso Argentina"
py scripts/fetch_cafci.py top "Renta Fija Peso Argentina" --limit 5

# ── FICHAS INDIVIDUALES ────────────────────────────────────────────────

# Ficha markdown (rendimientos TNA: 7d/1m/90d/180d/YTD/12m + datos del fondo)
py scripts/fetch_cafci.py ficha 304 308              # 1810 Ahorro
py scripts/fetch_cafci.py ficha 1717 5772            # otro fondo
py scripts/fetch_cafci.py ficha 304 308 -o ficha.md  # guarda markdown

# Composicion de cartera (top activos + porcentaje)
py scripts/fetch_cafci.py cartera 304 308
py scripts/fetch_cafci.py cartera 1717 5772

# Ficha COMPLETA todo-en-uno (combina catalogo + diario + ficha + cartera)
py scripts/fetch_cafci.py fondo 304 308
py scripts/fetch_cafci.py fondo 304 308 -o 1810_ahorro_completo.json

# ── COMBINADO ──────────────────────────────────────────────────────────

# Catalogo + diario juntos (sin fichas individuales)
py scripts/fetch_cafci.py all -o cafci_snapshot.json

# ── OUTPUT ─────────────────────────────────────────────────────────────

# Modo silencioso (solo JSON/markdown, sin logs)
py scripts/fetch_cafci.py top "Mercado de Dinero Peso Argentina" -q

Endpoints disponibles

ModoDataURL
catalogoCatalogo: 1152 fondos, 4615 clases, IDs, honorarios, metadataGET /consulta-de-fondos.json
diarioSnapshot diario: VCP, patrimonio, market share, variacionesGET /pb_get (XLSX)
ficha FONDO CLASEFicha markdown: rendimientos TNA por periodoGET defuddle.md/.../fondos/{F}?clase={C}
cartera FONDO CLASEComposicion de cartera (top activos + %)GET .../fondos/{F}?clase={C} (HTML)
buscar QUERYBuscar fondos por nombre parcial(local, sobre catalogo)
resolve QUERYResolver fondoId/claseId desde nombre(local, sobre catalogo)
top CATEGORIATop N por patrimonio en una categoria(local, sobre diario)
fondo FONDO CLASEFicha completa todo-en-uno (combina los 4 endpoints)(local + 4 requests)
allSnapshot catalogo + diario(local + 2 requests)

Total: 4 endpoints HTTP + 5 funciones de consulta sobre cache.


Cache local

Los datasets pesados (catalogo + diario) se cachean una vez por dia en el directorio temporal del sistema:

$TMP/cafci-catalog-YYYY-MM-DD.json    (~2.7 MB)
$TMP/cafci-daily-YYYY-MM-DD.json      (~1-2 MB)
  • Windows: C:\Users\<user>\AppData\Local\Temp\
  • Linux/Mac: /tmp/

Si vas a hacer multiples consultas en el dia (typical workflow), reusan el cache automaticamente. Forzar refetch con --no-cache.


Tipos de renta soportados

TipoCantidad fondos
Renta Fija542
Renta Mixta271
Mercado de Dinero96
Renta Variable76
PyMes65
Retorno Total42
Infraestructura23
Fondos Cerrados22
ASG10
RG9005

Categorias del DIARIO (para top)

Las categorias del diario combinan tipo_renta + moneda + region como string. Ejemplos comunes:

CategoriaCobertura
Renta Variable Peso ArgentinaAcciones argentinas
Mercado de Dinero Peso ArgentinaMoney Market $
Renta Fija Peso ArgentinaBonos $
Renta Fija Dolar Estadounidense ArgentinaBonos USD argentinos
Renta Mixta Peso ArgentinaFondos mixtos $
Retorno Total Peso ArgentinaTotal return $

Para ver lista completa: py scripts/fetch_cafci.py diario -q | jq '.categorias'


Consideraciones tecnicas

Top-level:

CampoDescripcion
generated_atTimestamp ISO del catalogo.
total_fondos, total_clasesContadores.
filtrosCatalogos de enums: tipo_renta, region, moneda, benchmark, duration, horizonte, sociedad_gerente, tipo_dinero, tipo_renta_mixta.
fondos[]Array de fondos.

Cada fondos[] tiene id, nombre, codigo_cnv, estado, objetivo, tipo_dinero, valuacion, dias_liquidacion, inicio, sociedad_gerente, sociedad_depositaria, moneda, tipo_renta, region, duration, benchmark, horizonte y clases[].

Cada clases[] tiene id, nombre, moneda, inversion_minima, honorarios (ingreso, rescate, transferencia, administracion_gerente, administracion_depositaria, gasto_ordinario_gestion), suscripcion, liquidez, rg384, log_abierto, ticker_bloomberg, ticker_isin.

⚠️ honorarios.* son strings (no floats). Castear con float() antes de comparar.

Show full SKILL.md (292 more words)Show less
Datos devueltos por diario
json
{
  "fecha_reporte": "2026-06-04",
  "categorias": ["Renta Variable Peso Argentina", ...],
  "fondos": [
    {
      "nombre": "Allaria Equity Selection - Clase A",
      "categoria": "Renta Variable Peso Argentina",
      "moneda": "ARS",
      "region": "Arg",
      "horizonte": "Cor",
      "fecha": "2026-06-04",
      "vcp_actual": 1642.85,
      "vcp_anterior": 1628.345,
      "variacion_dia_pct": 0.891,
      "vcp_reexp_pesos": 1642.85,
      "variacion_mes_pct": -1.181,
      "variacion_ytd_pct": 11.939,
      "variacion_12m_pct": 61.542,
      "cantidad_cuotapartes": 1276470413.29,
      "patrimonio": 2097049572.01,
      "market_share": 0.107,
      "depositaria": "Banco Comafi S.A.",
      "codigo_cnv": "1603"
    }
  ]
}
Datos devueltos por cartera
json
{
  "fondo_id": 304,
  "clase_id": 308,
  "fecha_cartera": "15/05/2026",
  "composicion": [
    {"nombre": "Cta Cte $ Rem Bco Credico", "porcentaje": 17.4},
    {"nombre": "Pzo Fi $ Bco Nacion", "porcentaje": 14.8},
    ...
    {"nombre": "Resto de Activos", "porcentaje": 29.2}
  ]
}

CAFCI publica solo los top ~14 activos + "Resto de Activos" agrupado. La fecha de cartera tiene delay de ~2-3 semanas vs el diario.

Datos devueltos por fondo (todo-en-uno)
json
{
  "meta": { ...del catalogo... },
  "diario": { ...del XLSX... },
  "ficha_md": "...markdown defuddle...",
  "cartera": { ...composicion... }
}
Workflows recomendados

A) Top N por patrimonio con fees:

  1. top "<categoria>" --limit N → lista de fondos
  2. Para cada nombre, resolve para conseguir fondo_id, clase_id
  3. Buscar honorarios en catalogo por clases[].nombre exacto

B) Ficha completa de un fondo:

  1. resolve "<query>" → conseguir IDs
  2. fondo FONDO_ID CLASE_ID → todo-en-uno

C) Cuando el usuario no especifica clase:

  • Usar buscar o resolve y mostrar las clases disponibles
  • Si hay una sola, continuar automaticamente con esa
Flags
FlagDescripcion
--limit NCantidad de resultados (top). Default: 10
--no-cacheForzar refetch de catalogo/diario (ignorar cache local)
-o archivoGuardar output a archivo JSON o markdown
-q / --quietModo silencioso (solo JSON/markdown, sin logs)
Rate limiting

No hay rate limiting documentado. Recomendado:

  • Minimo 0.3 segundos entre requests a CAFCI.
  • Para defuddle.md (proxy externo), esperar mas si hay timeouts.
  • Para batches grandes, usar pool de concurrencia max 5.
Manejo de errores
StatusCausas tipicas
200OK
403 Route not allowedPath discontinuado de la API REST anterior
403 (en /pb_get)Faltan headers de browser (Origin, Referer) — el script ya los envia
404URL mal formada o IDs inexistentes
Timeout en defuddle.mdProxy externo lento — reintentar
Encoding

UTF-8 valido. Las consolas Windows muestran ? para acentos pero los archivos UTF-8 se guardan correctamente (el script usa ensure_ascii=False).


Estructura del skill

skills/cafci/
├── SKILL.md                          # Este archivo (guia rapida)
├── references/
│   └── REFERENCE.md                  # Documentacion completa de los 4 endpoints + cache
└── scripts/
    └── fetch_cafci.py                # Script principal

Documentacion detallada: Consultar references/REFERENCE.md para schemas JSON completos, tablas de campos exhaustivas, codigos de tipo_renta/region/horizonte/moneda, cache local, manejo de errores y consideraciones tecnicas.

Inspirado en: ferminrp/agent-skills/cafci-fondos-comunes-argentina — esta implementacion porta el mismo diseño de 4 fuentes a la arquitectura SKILL.md / references/REFERENCE.md / scripts/fetch_*.py del repo.

© gauss314, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts, references) in skills/cafci of gauss314/skills.

  • SKILL.md
  • references/REFERENCE.md
  • scripts/fetch_cafci.py

Open the folder on GitHubat commit 5156f81

Compare with similar skills

Cafci next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Cafci compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Cafci this skillgauss314/skills248—~2.9kAutomated safety check: PassMIT
MarkitdownImCa0/just-laws78114 repos~3.2kAutomated safety check: NotesMIT
Data Table Managern8n-io/n8n207k—~2.3kAutomated safety check: PassCustom licence
Docx4jplutext/docx4j2.4k—~2.5kAutomated safety check: PassNone
Instrument Data To Allotropeaws-samples/amazon-bedrock-agents-healthcare-lifesciences2742 repos~2.7kAutomated safety check: PassApache-2.0
Cyber Pptcrazyykhllc-bit/CyberPPT1.8k—~10kAutomated safety check: PassMIT

Similar skills

  • Markitdown

    ImCa0/just-laws

    Convert files and office documents to Markdown. An agent skill from ImCa0/just-laws.

    781 GitHub starsUsed in 14 repos~3.2k tokens
    Documents & OfficeAuto-check: notes
  • Official

    Load before calling data-tables or parse-file. An agent skill from n8n-io/n8n.

    207k GitHub stars~2.3k tokensUpdated today
    Documents & OfficeAuto-check passed
  • Docx4j

    plutext/docx4j

    A skill your agent uses when writing Java code that creates, reads or edits Word (.docx), PowerPoint (.pptx) or Excel (.xlsx) files with docx4j — including generating documents, editing existing…

    2.4k GitHub stars~2.5k tokensUpdated yesterday
    Documents & OfficeAuto-check passed
  • Instrument Data To Allotrope

    aws-samples/amazon-bedrock-agents-healthcare-lifesciences

    Official

    Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV.

    274 GitHub starsUsed in 2 repos~2.7k tokens
    Documents & OfficeAuto-check passed
  • Cyber Ppt

    crazyykhllc-bit/CyberPPT

    当用户需要把 DOCX、PDF、TXT、XLSX、研究报告、业务材料或原始数据转成高密度、可编辑、咨询风格 PPTX 时使用;也适用于需要 SCR 论证、视觉风格探索、详细图表和渲染质检的 PPT。

    1.8k GitHub stars~10k tokensUpdated 2 mo ago
    Documents & OfficeAuto-check passed
  • Jev SEO

    AgriciDaniel/jev-seo

    Full live SEO audit of any website from its homepage URL, powered by Jev (TypeSafe's System One model).

    543 GitHub stars~2.5k tokensUpdated 18 days ago
    Documents & OfficeAuto-check: notes

More from gauss314/skills

All 32 skills in this repo
  • Backtesting

    gauss314/skills

    Academic backtesting framework for quantitative research. An agent skill from gauss314/skills.

    248 GitHub stars~2.4k tokensUpdated 3 mo ago
    Auto-check passed
  • Google Finance

    gauss314/skills

    Datos de Google Finance via batchexecute (API RPC interna sin auth ni API key).

    248 GitHub stars~3.1k tokensUpdated 3 mo ago
    Auto-check passed
  • Historyofmarket

    gauss314/skills

    History of Market (historyofmarket.com) — API publica con 88 datasets historicos de indices US desde 1871.

    248 GitHub stars~1.6k tokensUpdated 3 mo ago
    Auto-check passed
  • Indec

    gauss314/skills

    Datos macro y sociales de Argentina via la API oficial Series de Tiempo del Estado (apis.datos.gob.ar/series).

    248 GitHub stars~3k tokensUpdated 3 mo ago
    Auto-check passed
  • Morningstar

    gauss314/skills

    Morningstar Screener via API JSON publica: descarga masiva de 53 universes (102K+ listings, 39 paises, NYSE/Nasdaq/BCBA/etc) con 33 campos (precio, market cap, ratios, retornos…

    248 GitHub stars~2.6k tokensUpdated 3 mo ago
    Auto-check passed
  • Option Pricing

    gauss314/skills

    Pricing completo de opciones europeas y americanas. An agent skill from gauss314/skills.

    248 GitHub stars~4.7k tokensUpdated 3 mo ago
    Auto-check passed

Works with

Questions about Cafci

What does Cafci do?

Datos de fondos comunes de inversion argentinos via CAFCI (Camara Argentina de Fondos Comunes de Inversion). Cafci is an agent skill from gauss314/skills. Datos de fondos comunes de inversion argentinos via CAFCI (Camara Argentina de Fondos Comunes de Inversion).

When should I use Cafci?

Cafci fits situations like: tasks that involve Excel spreadsheets.

How do I install Cafci in Claude Code?

Run `npx skills add gauss314/skills --skill cafci -a claude-code`. Or copy the skill folder (skills/cafci in gauss314/skills) into .claude/skills/cafci in your project. Claude Code loads it when a task matches its description.

How do I install Cafci in Codex?

Run `npx skills add gauss314/skills --skill cafci -a codex`. Or copy the skill folder (skills/cafci in gauss314/skills) into .agents/skills/cafci in your project. Codex loads it when a task matches its description.

Can I use Cafci in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gauss314/skills --skill cafci -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cafci, .gemini/skills/cafci, .github/skills/cafci and .opencode/skills/cafci in your project.

What does Cafci need to run?

Going by SKILL.md and its folder, Cafci needs Python for the scripts in its folder and the command-line tools its instructions call (pip and jq). Our summary lists: Python 3.

Does Cafci access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Cafci safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Cafci use?

Cafci is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cafci use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.4k tokens, read only when the agent opens those files.

What are the alternatives to Cafci?

Skills that share tags, products or a category with Cafci: Markitdown (ImCa0/just-laws, 781 stars), Data Table Manager (n8n-io/n8n, 207k stars), Docx4j (plutext/docx4j, 2.4k stars) and Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cafci?

gauss314 (a GitHub user) maintains it in gauss314/skills, which has 248 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 14, 2026.

Source: gauss314/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.