Hacktoberfest 2026: los issues que los mantenedores marcaron para octubre, abiertos y aptos para principiantes. Explorar issues de Hacktoberfest

[curriculum-eval] side-quest-11-06-anthropic-key.md: cognitive_load — highest concept density in corpus despite short word count

Cerrado Apto para principiantes
#4,488 0 comentarios 0 reacciones 0 asignados Ver en GitHub

Los mantenedores suelen responder en 1 día

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
2/5
Tiempo estimado
1-3 horas
Aptitud para principiantes
72/100
Tipo de issue
Documentación
Claridad
Bien especificado
Estado de actividad
Activo
Stack tecnológico
markdown

Línea de trabajo

Lee workshop/side-quest-11-06-anthropic-key.md y aplica los tres cambios solicitados: reducir la terminología repetida, unir los bloques de advertencia contiguos y añadir un elemento a la lista de verificación para copiar la clave. Mantén sin cambios los bloques de código y la sección final Checkpoint; después, ejecuta markdownlint-cli2. La tarea estará terminada cuando los cambios aborden esos puntos y el comando de lint se ejecute correctamente.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

curriculum documentation quality

File: workshop/side-quest-11-06-anthropic-key.md
Overall Score: 5.37 / 10.0 (corpus mean: 6.09)

Flagged Dimensions:

Dimension Score Benchmark Delta
cognitive_load 7.2 ≤ 15 new concepts −5.5 concept penalty (26 new concepts in only 673 words)
active_learning 3.4 density ≥ 3 −6.6 (density 1.04; 2 code blocks + 5 checklist items)

Root Cause (≤ 2 sentences):
Despite being one of the shortest pages in the corpus (673 words), this page has the highest new-concept density of all five findings — 26 bolded/code terms (ANTHROPIC_API_KEY, engine: claude, api.anthropic.com, network.allowed, etc.) packed into a short page via a dense "What you'll set up" table, two nested <details> warning blocks, and a "Common mistakes" list, each introducing its own vocabulary. This terminology-per-word ratio overloads working memory even though total reading time is short.

Evidence (quoted from the file):

"| Item | Value | |---|---| | Repository secret name | ANTHROPIC_API_KEY | | Frontmatter engine field | engine: claude | | Anthropic API domain | api.anthropic.com |" (three new terms in one table, immediately followed by a 3-step key-generation flow, a save-the-key warning, a billing warning, a 6-step secret-storage flow, a mistakes list, and a frontmatter block)

Learning Science Rationale:
Cognitive Load Theory's "element interactivity" concept holds that load scales with how many new elements must be held in mind simultaneously to understand a procedure, not just text length — this page's terms (secret name, frontmatter key, domain, billing unit) all interact in a single mental model the learner must track at once. Consolidating redundant restatements of ANTHROPIC_API_KEY (it already appears in the summary table, the step list, the tip, and the common-mistakes list) into a single reference point reduces element interactivity without removing information.

Improvement Prompt (for an agent):

Edit workshop/side-quest-11-06-anthropic-key.md to reduce concept density:
1. Keep the "What you'll set up" summary table as the single canonical reference for
   ANTHROPIC_API_KEY, engine: claude, and api.anthropic.com. Remove the duplicate
   restatement of the exact secret name from the ":pencil2:" step list and the
   "Common mistakes" list; instead have those sections say "see the secret name above."
2. Merge the two <details> warning blocks ("Key is shown only once" and the billings
   NOTE callout right after it) into a single callout so the page has one, not two,
   back-to-back warnings before the main task starts.
3. Add one short checklist item directly under "Get an Anthropic API key" confirming
   the learner copied the key, before moving to "Store the key as a repository secret",
   to turn passive reading into an active checkpoint mid-page rather than only at the end.
Keep all code blocks and the final Checkpoint section unchanged. Re-run
markdownlint-cli2 after editing.

Expected Score After Fix: 6.2–6.6 / 10.0

Generated by 🔬 Curriculum Quality Evaluator · copilot · auto · 119.1 AIC · ⌖ 17.8 AIC · ⊞ 10.4K · ◷

  • expires on Oct 13, 2026, 4:04 AM UTC
Lenguaje dominante
JavaScript
Estrellas
53
Forks
35
Merge medio
1 d 5 h
PR fusionados (30 d)
16

Preparar el entorno

Abrir en Codespaces

Inicia el contenedor de desarrollo del proyecto en tu navegador, con tu propia cuenta de GitHub.

  • Sin Dockerfile ni archivo de Docker Compose
  • Sin plantilla de pull request
  • Sin guía de contribución

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Más de githubnext/gh-aw-workshop

Todos los issues de githubnext/gh-aw-workshop

Issues similares

Más issues de JavaScript

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.