agentleFS
aaronjmarsaaronjmars/miroshark-aeon/skills/digest/SKILL.md

digest

Skill20 starsChanged 23 days agoMITView on GitHub

Generate and send a digest on a configurable topic, optionally pulling RSS/Atom feeds as an input source alongside web + X signal

  • Reads credentials

33 other projects use a version of this, 2 of them edited.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

12 rules. 0 are common, 3 are distinctive, and 9 are very specific to this project.

  • 0

    Common

    Most of the 28 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 9

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read memory/MEMORY.md for high-level context and tracked topics, and scan the last 3 days of memory/logs/ so you can dedup against anything …

    line 30
  2. Very specific:

    Read memory/feeds.yml for the feed list.

    line 88
  3. Very specific:

    If sources = rss and there are no new items across all feeds, log RSS_DIGEST_OK in the run log and end without notifying.

    line 96
  4. Very specific:

    Already covered in the last 3 daily logs?: Check memory/logs/ for entries from the last 3 days.

    line 105
  5. Distinctive:

    Two sources telling the same story?: Keep one — prefer the primary source (announcement post, repo release, official filing) over the recap.

    line 106
  6. Very specific:

    Alternate RSS layout (RSS-only runs): when sources = rss, you may instead group items by feed name if that reads better than a single …

    line 142
  7. Very specific:

    Before calling ./notify, walk this checklist mentally:

    line 159
  8. Very specific:

    Write the digest body to a file (e.g.

    line 172
  9. Very specific:

    Update memory/MEMORY.md "Recent Digests" table with one row: date, topic (or ${var}), key topics (3 short keywords).

    line 182
  10. Distinctive:

    Never send a digest with placeholder links or "TBD" sections.

    line 206
  11. Distinctive:

    Never invent items to hit a target count.

    line 207
  12. Very specific:

    Never repeat a story already in the last 3 days of memory/logs/ unless there's a material update — and say so explicitly when you do.

    line 208

“Common” is measured: kept by at least 6 in 10 of the 28 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- autoresearch: variation B — curatorial discipline (filter → distill → structure → sanity-check) folded with direct-curl xAI + web/RSS inputs and memory-aware dedup; RSS feed-reading + item-selection absorbed from rss-digest as an additional source class -->

${var} — Selects the digest's topic and which source classes feed it. Grammar:

  • "" (empty) → digest's default sources (WebSearch + xAI/Grok + aggregators), no topic filter — a broad daily digest.
  • "<topic>" → topic-focused digest on the default web sources, filtered to <topic> (e.g. "solana", "AI agents", "rust").
  • "rss" → RSS-only: pull feeds from memory/feeds.yml, no topic filter.
  • "rss: <topic>" → RSS-only, filtered to <topic> (e.g. "rss: rust").
  • "<topic> +rss" → default web sources and RSS feeds combined, both filtered to <topic> (e.g. "AI agents +rss").

Today is ${today}. Generate and send a daily ${var} digest.

The whole point of a digest is signal, not volume. A reader skimming for 60 seconds should walk away with three things they didn't know that morning and one of them should change a decision they'd make this week. Anything that doesn't clear that bar gets cut.

Preamble — orient and parse the selector

  1. Read memory/MEMORY.md for high-level context and tracked topics, and scan the last 3 days of memory/logs/ so you can dedup against anything already reported.
  2. Parse ${var} into {topic, sources}:
    • Strip a trailing +rss → adds RSS to the default web sources. Remainder is the topic.
    • A leading rss: (or the bare token rss) → RSS-only source set; text after the colon is the topic (empty = no filter).
    • Otherwise the whole string is the topic and sources = default web (empty string = default web, no topic filter).
    • Resulting sources is one of: web (default), rss (RSS-only), or web+rss (both).
  3. The topic, when non-empty, is a filter applied to every source class — web queries are scoped to it and RSS items must match it (title/description/tags). Empty topic = keep all relevant items.

Config (RSS source)

When sources includes rss, this skill reads feed URLs from memory/feeds.yml. If the file doesn't exist yet, create it (write mode) with the shape below, or — if you have nothing to seed it with — log a one-line note and treat the RSS source as empty for this run.

# memory/feeds.yml
feeds:
  - name: Example Feed
    url: https://example.com/rss
  - name: Another Feed
    url: https://example.com/atom.xml

Phase 1 — Gather (cast a wide net)

Pull from the source classes selected by ${var}. Never rely on a single one — if sources = web, use at least two of the web classes below; if sources = web+rss, RSS counts as one class and you still want a second.

Web sources (active when sources is web or web+rss)

  1. WebSearch (built-in) — run 2 distinct queries:
    • "${topic}" news ${today} (broad). If topic is empty, run a general query for the day's notable stories in the operator's tracked areas (from memory/MEMORY.md).
    • One narrower query you choose based on ${topic} (e.g. for "solana" → "solana" launches OR funding OR exploit ${today}; for "AI agents" → "agent framework" OR "agentic" release ${today}).
  2. xAI x_search via Grok — pulls the X/Twitter signal layer. XAI_API_KEY is injected into this skill's environment (declared in requires:) and is the primary path; see Fetching the X signal below for the full contract (attempt the curl before any fallback, set the Bash tool timeout ≥180000, record the true failure reason).

    Path A - X.AI API (primary): a direct curl to the Responses API. First confirm the key as Fetching the X signal rule 1 says (the run notes' "Keys set for this run" line, no shell test); if KEY_PRESENT (it will be), this path is required. When you run the curl, set the Bash tool's timeout to at least 180000.

    Shell shape. Each Bash call is one allowed command (pipes are fine). The run refuses a call that sets a variable (FROM_DATE=$(date ...), PROMPT="...", HTTP=$(./secretcurl ...)), uses [ ... ] && tests, or joins commands with ;, && or ||, and each refusal costs a model turn. So get each date with a bare date call, write the printed values and the topic into later commands literally (the <FROM_DATE>, <TO_DATE>, <TOPIC> placeholders), and build the payload with one jq -n call piped straight into one ./secretcurl call. A > redirect into a file and a $name in a jq filter (--arg p ... '$p') are refused too, so the topic and dates go into the filter as plain JSON strings (a " inside the topic becomes \", and reword any ').

    Get the window dates first, each date as its own Bash call:

    date -u -d yesterday +%Y-%m-%d
    date -u +%Y-%m-%d

    The first prints FROM_DATE, the second TO_DATE. Build the payload with the prompt inline and pipe it into the send in the same call (it prints the HTTP status; ./secretcurl also prints an http=... bytes=... line on stderr); <TOPIC> is the parsed topic, or the most notable technology, AI, and crypto stories today when the topic is empty:

    jq -n '{model:"grok-4.7", input:[{role:"user",content:"Search X for substantive, recent posts about: <TOPIC>. Date range: <FROM_DATE> to <TO_DATE>. Return up to 10 high-signal posts - prioritize verifiable claims, launches, funding, releases, exploits, or hard data over hot takes. For EACH post return: @handle, the full text, date posted, exact engagement counts (likes, retweets, replies; 0 if unknown), and the direct link https://x.com/handle/status/ID. Return a numbered list."}], tools:[{type:"x_search",from_date:"<FROM_DATE>",to_date:"<TO_DATE>"}]}' \
      | ./secretcurl -s -o /tmp/xai-digest.json -w '%{http_code}' --max-time 150 -X POST "https://api.x.ai/v1/responses" \
      -H "Content-Type: application/json" -H "Authorization: Bearer {XAI_API_KEY}" --data-binary @-

    On HTTP=200 with a non-empty body, parse it with jq -r '.output[] | select(.type == "message") | .content[] | select(.type == "output_text") | .text' and feed each post (handle, text, engagement, permalink) into the web-candidate pool. A slow curl is not a missing key — do not treat a timeout as key-unavailable.

    Path B - WebFetch/WebSearch fallback (last resort, lower quality): only if the key is KEY_UNSET, or Path A returned a non-2xx / empty body / timeout. Attempt a WebFetch to a public X search URL like https://x.com/search?q=${topic}&f=live, or a site:x.com "<topic>" after:<FROM_DATE> WebSearch; extract a few top posts and prefer results within the last 48h. Record the true reason (key-unset | http-<code> | empty | timeout) in the log - never "XAI_API_KEY unavailable" when the key was set. If this also returns nothing, skip the X source for this run.

  3. WebFetch on a topic-relevant aggregator (only if WebSearch returned thin results): e.g. https://news.ycombinator.com/, https://www.reddit.com/r/<topic>/top/?t=day.json, or a known feed for the topic.

Aim for ~15 raw web candidates at this stage. More is fine; fewer than 8 is a warning sign — broaden your queries before moving on.

RSS source (active when sources is rss or web+rss)

Read memory/feeds.yml for the feed list. For each feed in feeds.yml:

  1. Fetch the RSS/Atom XML: curl -sL "FEED_URL". If curl fails, fall back to WebFetch on the same URL.
  2. Parse for entries published in the last 24h (check <pubDate> or <updated> tags).
  3. Extract title, link, and description for each new entry.

Deduplicate against recent logs (see Phase 2). From all new entries, select the 5–7 most interesting items — prioritize topics tracked in memory/MEMORY.md, and apply the ${topic} filter when set (title/description/tags must match). For each selected item, if the summary is too thin, use WebFetch to pull the full article, then write a 1–2 sentence note on why it matters. These become RSS candidates entering the shared pipeline below.

If sources = rss and there are no new items across all feeds, log RSS_DIGEST_OK in the run log and end without notifying.

Phase 2 — Filter (kill the noise)

Pool every candidate (web + RSS) and drop any that fails a single check:

  • No source link? Drop it. Every surviving item must have a clickable URL (article URL, feed entry link, or https://x.com/handle/status/ID).
  • Older than 36 hours? Drop it unless it's a still-developing story being re-surfaced for a new reason. (RSS entries are already scoped to the last 24h; this catches stale web results.)
  • Pure speculation, hot take, or "X reacts to Y"? Drop it. Keep things with a verifiable claim, named entity, number, release, or transaction.
  • Already covered in the last 3 daily logs? Check memory/logs/ for entries from the last 3 days. If the same story (same headline subject, same primary actor) appears, drop the duplicate unless there's a material new development to report.
  • Two sources telling the same story? Keep one — prefer the primary source (announcement post, repo release, official filing) over the recap. A web hit and an RSS entry on the same event count as duplicates; keep the primary.

Target: ~5–8 survivors after this pass.

Phase 3 — Distill and structure (force the shape)

Pick the 3–5 strongest items. Lead with the single most actionable one — the item where a reader can do something today (subscribe, sell, fork, attend, apply, watch). Then descend by importance.

Format the digest exactly like this (unified format — used for web, rss, and web+rss runs):

*${var} — ${today}*

_TL;DR: <one sentence covering the day's gravity. Concrete, no adjectives.>_

1. *<Headline-style title, ≤90 chars>*
   <1–2 sentence summary. Lead with what happened, not who said it.>
   Why it matters: <one short clause — concrete consequence, not vibes>
   <link>

2. *<Title>*
   ...

3. *<Title>*
   ...

(Optional, only if there's genuine secondary signal:)
*Also worth a glance:* <1-line bullet> · <1-line bullet>

Format rules:

  • Markdown only. No emoji. No "Here's your digest" preamble.
  • Total length: ≤3000 chars (the old 4000 was too loose — discipline forces cuts).
  • Every item: title + summary + link. Include a "Why it matters" line whenever you can state a concrete consequence (price impact, user-facing change, upstream dependency, deadline, precedent). If you can't write one without hand-waving, omit the line — do not replace it with filler like "this could be significant" or "watch this space".
  • On thin-news days where fewer than 3 items clear the bar: log DIGEST_FETCH_EMPTY (or DIGEST_THIN if 1–2 items survived) in the run log and skip the notification rather than padding.

Alternate RSS layout (RSS-only runs): when sources = rss, you may instead group items by feed name if that reads better than a single ranked list — this preserves the original RSS-digest presentation:

*RSS Digest — ${today}*

*Feed Name*
- [Title](url) — summary
- [Title](url) — summary

*Feed Name*
- [Title](url) — summary

The grouped RSS layout stays ≤4000 chars. Prefer the unified ranked format when the run mixes sources (web+rss) so the reader gets one prioritized list.

Phase 4 — Sanity-check (last pass before sending)

Before calling ./notify, walk this checklist mentally:

  • Lead item is the most actionable one I have, not just the most dramatic.
  • Every link resolves to a real URL (no [link] placeholders, no truncated IDs).
  • No item is paraphrasing a hot take — each has a verifiable underlying fact.
  • No two items are the same story under different angles (including a web hit + an RSS entry on the same event).
  • Char count under the limit for the chosen format (3000 unified / 4000 grouped RSS).
  • No emoji slipped in. No corporate hedging ("could potentially", "it remains to be seen").

If the digest fails any check, fix it before sending. If after filtering you have fewer than 3 strong items, do not pad — send a shorter "thin day" digest with whatever survived and a one-line note acknowledging it was a quiet news day. Do not invent or stretch.

Phase 5 — Send and log

  1. Write the digest body to a file (e.g. /tmp/digest.md) with the Write tool (not a shell redirect) and send it with ./notify -f /tmp/digest.md (a long multi-line argv trips the sandbox; -f keeps it short).
  2. Append to memory/logs/${today}.md under one ### digest heading:
    ### digest (${var})
    - Source mode: <web | rss | web+rss>
    - Sources used: <list — e.g. WebSearch, xAI API (api|fallback:reason), feeds.yml (Feed A, Feed B)>
    - Raw candidates: <N> (web <Nw> / rss <Nr>), after filter: <M>, sent: <K>
    - Lead item: <title>
    - Notes: <anything unusual — xAI fetch fallback + true reason (http-<code>/empty/timeout/key-unset), thin day (DIGEST_THIN/DIGEST_FETCH_EMPTY), RSS_DIGEST_OK, dedup against prior log>
  3. Update memory/MEMORY.md "Recent Digests" table with one row: date, topic (or ${var}), key topics (3 short keywords).

Fetching the X signal

XAI_API_KEY is injected into this skill's environment (declared in requires:) and is present and valid. The primary way to pull the X/Twitter signal layer is a direct curl to https://api.x.ai/v1/responses with Authorization: Bearer {XAI_API_KEY} (see Phase 1 → Path A). There is no network sandbox blocking this — just make the call.

Rules:

  1. Check, don't assume. Read the "Keys set for this run" line in your run notes, never a shell test (those are refused and cost a turn): XAI_API_KEY on that line = KEY_PRESENT, not on it = KEY_UNSET. If KEY_PRESENT (it will be), Path A is required before any fallback.
  2. Allow enough time. Grok's x_search typically takes 30–120s (it searches X live). Set the Bash tool's timeout to at least 180000 (180s) for the curl, and keep --max-time 150 on the curl itself so it fails cleanly rather than hanging. A slow curl is not a missing key — never treat a timeout as key-unavailable.
  3. Capture the HTTP status and parse the body with the standard jq extractor (jq -r '.output[] | select(.type == "message") | .content[] | select(.type == "output_text") | .text'). HTTP=200 + non-empty body → use it.
  4. Fall back only on a real failure, recording the true reason: key-unset (only if step 1 said KEY_UNSET), http-<code> (non-2xx), empty (200 but nothing parsed), or timeout (curl exceeded --max-time). Never log "XAI_API_KEY unavailable" when the key was set.

WebFetch / WebSearch are last-resort fallbacks only for the X signal (lower quality — WebSearch favours older high-engagement posts). Never reach for them while the key works.

RSS feeds & public aggregators (no auth): fetch with curl -sL; if that fails intermittently, the built-in WebFetch tool is a reliable fallback for any feed URL, aggregator (HN, Reddit JSON, news sites), or article. This is a convenience fallback for unauthenticated URLs, not a sandbox workaround. A digest built from WebSearch + reachable RSS alone is still valid — note it in the log so health checks can spot the pattern.

Environment Variables Required

  • XAI_API_KEY — X.AI API key for Grok's x_search. Declared in requires:, so it is injected into this skill's environment and is the primary path for the X signal layer (direct curl; see Fetching the X signal). Optional overall — digest still works on web + RSS sources alone if it is ever unset.
  • Notification channels configured via repo secrets (see CLAUDE.md).

Constraints

  • Never send a digest with placeholder links or "TBD" sections.
  • Never invent items to hit a target count. Fewer good items beats more weak ones.
  • Never repeat a story already in the last 3 days of memory/logs/ unless there's a material update — and say so explicitly when you do.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.