Skip to main content

replace-skill-name

Digest of the most interesting new posts on [REPLACE: TOPIC] from RSS feeds and the open web

Ir a la instalación

Datos de origen

Repositorio
aeonfun/aeon
Última actividad en el origen
4 de agosto de 2026 a las 21:01
Idioma detectado de SKILL.md
inglés
Estrellas
738
Forks
265

Opciones de instalación

De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.

Revisa los archivos de origen

Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.

Mostrando SKILL.md

SKILL.md
Instrucciones de origen · Vista previa de solo lectura
name
[REPLACE: SKILL_NAME]
description
Digest of the most interesting new posts on [REPLACE: TOPIC] from RSS feeds and the open web
> **${var}** — Optional. Pass a different topic to override the default. If empty, digests [REPLACE: TOPIC]. Today is ${today}. Build a digest of the [REPLACE: MAX_ITEMS] most interesting new posts on **[REPLACE: TOPIC]**. ## Steps 1. **Read sources** — pull the last 24h of entries from each feed: ```text [REPLACE: FEED_URLS] ``` (Comma- or newline-separated list of RSS/Atom URLs.) Use **WebFetch** to retrieve each feed and parse the entries. If a feed 404s or returns malformed XML, log a single warning line and skip that feed for this run. 2. **Augment with web search** — run a `WebSearch` for `[REPLACE: TOPIC] latest` and pick up to 5 fresh links published in the last 24h that aren't already in the feed results. 3. **Score and rank** — for each candidate, score on: - **Recency** — within the last 24h gets full marks. - **Source weight** — feeds in the configured list outrank generic search results. - **Specificity** — items mentioning concrete numbers, code, or named systems beat opinion pieces. Drop anything obviously off-topic (the `${var}` or `[REPLACE: TOPIC]` keyword should appear somewhere in title or summary). 4. **Pick the top [REPLACE: MAX_ITEMS]** — write `output/articles/[REPLACE: SKILL_NAME]-${today}.md` with one entry each: ```markdown ### [Title](url) *[Source · published date]* 2-3 sentences distilling the takeaway. No filler. ``` 5. **Notify** via `./notify` with: ``` *[REPLACE: TOPIC] digest — ${today}* [N] picks. Top item: [shortened title]. Full digest: https://github.com/${GITHUB_REPOSITORY}/blob/main/output/articles/[REPLACE: SKILL_NAME]-${today}.md ``` 6. **Log** — append to `memory/logs/${today}.md`: ``` ## [REPLACE: SKILL_NAME] - **Sources scanned**: N feeds + 1 web search - **Items picked**: N (of M candidates) - **Top source**: domain - **Status**: DIGEST_OK | DIGEST_QUIET (no items) | DIGEST_DEGRADED (some feeds failed) ``` ## Network note `WebFetch` and `WebSearch` are built-in Claude tools. There is no network sandbox — `curl` works too; use `WebFetch` as the fallback for a flaky public GET. For this research skill the reads are unauthenticated, so `WebSearch` + `WebFetch` are the simplest path. ## Constraints - **Never repeat**. Track which item URLs went out via `memory/topics/[REPLACE: SKILL_NAME]-seen.txt` (append-only). Skip anything that's already in there. - **No filler**. If fewer than `[REPLACE: MAX_ITEMS]` items meet the bar, send fewer items — never pad with low-signal content. - **Quote, don't paraphrase the news**. Say "Anthropic released X" not "AI labs are releasing things." Specificity beats hand-waving.
Ver en GitHub