X/Twitter Research via Grok
artwist-polyakov/polyakov-claude-skills
Searches X/Twitter through the xAI Grok API to build digests, trend reports and thread analysis, meant to surface post ideas for a Telegram channel.
Draft copy-paste-ready X replies - two options per reply-worthy tweet from tracked accounts, topics, or lists (default), or ready-to-post responses to engagement opps in recent logs (from-logs)
$ npx skills add aeonfun/aeon --skill reply-maker -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aeonfun/aeon reply-maker --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aeonfun/aeon.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/reply-maker .claude/skills/reply-maker && rm -rf skills-srcUse ~/.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/
Install the "reply-maker" agent skill from https://github.com/aeonfun/aeon/tree/main/skills/reply-maker into .claude/skills/reply-maker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reply-maker", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aeonfun/aeon/tree/main/skills/reply-makerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aeonfun/aeon --skill reply-maker -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aeonfun/aeon reply-maker --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aeonfun/aeon.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/reply-maker .agents/skills/reply-maker && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "reply-maker" agent skill from https://github.com/aeonfun/aeon/tree/main/skills/reply-maker into .agents/skills/reply-maker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reply-maker", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aeonfun/aeon --skill reply-maker -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aeonfun/aeon reply-maker --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aeonfun/aeon.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/reply-maker .cursor/skills/reply-maker && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "reply-maker" agent skill from https://github.com/aeonfun/aeon/tree/main/skills/reply-maker into .cursor/skills/reply-maker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reply-maker", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aeonfun/aeon.git --path skills/reply-maker--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aeonfun/aeon --skill reply-maker -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aeonfun/aeon reply-maker --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aeonfun/aeon.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/reply-maker .gemini/skills/reply-maker && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "reply-maker" agent skill from https://github.com/aeonfun/aeon/tree/main/skills/reply-maker into .gemini/skills/reply-maker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reply-maker", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aeonfun/aeon reply-makerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aeonfun/aeon --skill reply-maker -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aeonfun/aeon.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/reply-maker .github/skills/reply-maker && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "reply-maker" agent skill from https://github.com/aeonfun/aeon/tree/main/skills/reply-maker into .github/skills/reply-maker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reply-maker", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aeonfun/aeon --skill reply-maker -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aeonfun/aeon reply-maker --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aeonfun/aeon.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/reply-maker .opencode/skills/reply-maker && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "reply-maker" agent skill from https://github.com/aeonfun/aeon/tree/main/skills/reply-maker into .opencode/skills/reply-maker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reply-maker", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
reply-makerDraft copy-paste-ready X replies - two options per reply-worthy tweet from tracked accounts, topics, or lists (default), or ready-to-post responses to engagement opps in recent logs (from-logs)
Reply Maker is an agent skill from aeonfun/aeon. Draft copy-paste-ready X replies - two options per reply-worthy tweet from tracked accounts, topics, or lists (default), or ready-to-post responses to engagement opps in recent logs (from-logs)
Its SKILL.md is about 6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Writing & Content, covering Social media posts. It works with X (Twitter) and Telegram. The repository describes itself as: The most autonomous AI agent framework: runs unattended on GitHub Actions, self-healing skills, drives Claude Code, Grok, Codex & more. No approval loops. Configure once, forget… The licence is MIT.
7 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f252074. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
jqmakeFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
api.x.aix.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
XAI_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Reply Maker loads about 6k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 2,612 words of instructions outside code blocks.
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.
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); files beside SKILL.md are not scanned.
The full file from aeonfun/aeon at commit f252074, republished under its MIT licence (© aeonfun). 2,612 words, ~6,018 tokens.
.claude/skills/reply-maker/SKILL.md (or your agent's skills folder).<!-- autoresearch: variation B — sharper output via specificity gates, anti-sycophancy lint, post-write self-edit, and skip-gate for low-leverage tweets -->
${var} — selects the mode and scope:
- empty → Mode A (Reply Drafting): auto-discover reply-worthy tweets across your areas of interest (from recent logs + memory) and draft two reply options for each.
@handle/ numeric X list ID / topic → Mode A (Reply Drafting) scoped to that handle, list, or topic.from-logs(or--from-logs, optionally followed by an@handleor project name to narrow the scan) → Mode B (From-Logs Engagement): scan recent logs for flagged engagement opportunities and turn them into copy-paste-ready responses.revise:<instruction>→ Revise branch: reload the last drafted replies and refine them per the instruction (the Telegram force-reply shape, e.g.revise:make them shorter).
Read memory/MEMORY.md for context on active projects and open engagement follow-ups.
Then read memory/logs/ — the window depends on the mode:
memory/logs/ for recent fetch-tweets, narrative-tracker, and prior reply-maker outputs (used as a candidate pool and for reply de-duplication).memory/logs/ for engagement opportunities flagged by other skills (mention-radar, fetch-tweets, reply-maker) or noted in MEMORY.md "Known Follow-ups".Parse ${var} to pick the branch (trim whitespace, compare case-insensitively):
${var} starts with revise: — run the Revise branch (below) and stop. This is the shape scripts/telegram-route.sh sends when the operator replies to a "refine these replies?" force-reply prompt; catch it before mode parsing.${var} is from-logs or --from-logs — optionally followed by a whitespace-separated @handle or project name — run Mode B (From-Logs Engagement). Treat any trailing token as an optional filter that narrows the opportunity scan to that handle/project.${var} as the scope: empty, @handle, numeric X list ID, or a topic string.If soul files exist (soul/SOUL.md, soul/STYLE.md, soul/examples/), read them and mirror that voice in every reply. Match sentence length, vocabulary choices, punctuation habits, and the kinds of things the operator would never say.
If no soul files exist (or the bodies are empty placeholders), write replies that are:
Either way, when responding to someone who cosigned/mentioned/attributed the operator (Mode B): acknowledge without groveling — no "thanks so much for the kind words!", just the actual response.
revise:… — Telegram force-reply)The operator tapped the "refine these replies?" prompt and sent a free-text revision instruction. Handle it before Mode A/B:
${var#revise:} (keep any inner colons). Trim whitespace — e.g. make them shorter, less formal, drop reply B on #2.memory/drafts/reply-maker-latest.md — the stable path every normal run saves to (see the save steps in A4 / B6). If it's missing or empty, there's nothing to refine: send ./notify "Nothing to revise yet — run reply-maker first, then reply here to refine the drafts." and end the run.soul/ for voice, then regenerate the saved replies applying the operator's instruction. Keep the same set of target tweets and the same A/B two-option structure (Mode A) or ready-to-post list (Mode B) — you're refining wording, not re-discovering candidates. Re-enforce the hard reply rules: ≤280 chars for X replies, no sycophancy (see Banned sycophancy phrases), specifics not gestures.memory/drafts/reply-maker-latest.md (overwrite), so a further revise: refines the newest version../notify in the same format the originating mode uses, with a first line flagging it as a revision, e.g. revised (${var#revise:}):. Use ./notify -f <file> for multi-line output../notify "Want another pass? Reply with a change and I'll revise again." \
--force-reply --placeholder "e.g. make them shorter" \
--context "reply-maker::revise"### reply-maker with - **Mode:** revise and the instruction (see Log), then end the run — do NOT run Mode A or B.Generate two reply options for 5 reply-worthy tweets from tracked X accounts, a list, or a topic.
Goal: assemble 10–15 candidates posted in the last 6 hours (the high-leverage reply window — the algorithm rewards early replies, and the OP is still likely to engage back). Recency fallback: if the 6h window yields fewer than 3 candidates after the skip gate, widen to 12h and retry before failing the run.
For every candidate, capture: @handle, full tweet text, tweet URL, posted_at (ISO), engagement counts (likes, replies, retweets if available), and a one-line why-this-tweet note.
Path A — X.AI API (primary). XAI_API_KEY is injected into this skill's environment (declared in requires:), so the direct curl to https://api.x.ai/v1/responses is the primary fetch path (full contract in Fetching at the bottom). Preflight the key, then call Grok's x_search, capturing the HTTP status so any fallback decision is fact-based. x_search searches X live and takes 30–120s — set the Bash tool timeout to ≥180000 when you run this (a slow curl is not a missing key).
[ -n "$XAI_API_KEY" ] && echo KEY_PRESENT || echo KEY_UNSET
TO_DATE=$(date -u +%Y-%m-%dT%H:%M:%SZ)
FROM_DATE=$(date -u -d "6 hours ago" +%Y-%m-%dT%H:%M:%SZ 2>/dev/null || date -u -v-6H +%Y-%m-%dT%H:%M:%SZ)If KEY_PRESENT (it will be), Path A is required. Build the payload file /tmp/xai-rm-payload.json per ${var} (three shapes below — each branch writes the same fixed file), then:
HTTP=$(./secretcurl -s -o /tmp/xai-rm.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}" -d @/tmp/xai-rm-payload.json)
echo "xai http=$HTTP bytes=$(wc -c </tmp/xai-rm.json)"On HTTP=200 with a non-empty body, parse /tmp/xai-rm.json and mark xai=ok:
jq -r '.output[] | select(.type == "message") | .content[] | select(.type == "output_text") | .text' /tmp/xai-rm.jsonThe payload file /tmp/xai-rm-payload.json depends on ${var}. Whichever branch matches, build it with jq -n --arg (never a shell-interpolated string) and write it to that one fixed path — the ./secretcurl call above then sends it with -d @/tmp/xai-rm-payload.json:
If ${var} looks like an X list ID (numeric):
LIST_ID="${var}"
jq -n --arg list_id "$LIST_ID" --arg from "$FROM_DATE" --arg to "$TO_DATE" '{
model: "grok-4.7",
input: [{role: "user", content: ("Look at X list https://x.com/i/lists/" + $list_id + ". Return the 12 most reply-worthy original posts (not retweets, not replies) by members of this list between " + $from + " and " + $to + ". Reply-worthy = has a take, claim, question, or framing worth engaging — NOT pure self-promo, breaking news without analysis, or threads already past 500 replies. For each: @handle, full tweet text, tweet URL, posted_at ISO timestamp, like/reply/retweet counts.")}],
tools: [{type: "x_search", from_date: $from, to_date: $to}]
}' > /tmp/xai-rm-payload.jsonIf ${var} looks like a @handle — same query intent, scoped to that handle's recent original posts:
HANDLE="${var}"
jq -n --arg handle "$HANDLE" --arg from "$FROM_DATE" --arg to "$TO_DATE" '{
model: "grok-4.7",
input: [{role: "user", content: ("Look at recent original posts (not retweets, not replies) by " + $handle + " on X between " + $from + " and " + $to + ". Return the 12 most reply-worthy. Reply-worthy = has a take, claim, question, or framing worth engaging — NOT pure self-promo, breaking news without analysis, or threads already past 500 replies. For each: @handle, full tweet text, tweet URL, posted_at ISO timestamp, like/reply/retweet counts.")}],
tools: [{type: "x_search", from_date: $from, to_date: $to}]
}' > /tmp/xai-rm-payload.jsonIf ${var} is a topic (or empty) — same query intent with ${var} (or the top 2–3 topics from memory/MEMORY.md when empty) as the search query. When empty, also pull tweet candidates surfaced in the last 2 days of fetch-tweets logs as a backup pool.
TOPIC="${var}" # when empty, substitute the top 2–3 topics from memory/MEMORY.md
jq -n --arg topic "$TOPIC" --arg from "$FROM_DATE" --arg to "$TO_DATE" '{
model: "grok-4.7",
input: [{role: "user", content: ("Search X for the 12 most reply-worthy original posts (not retweets, not replies) about " + $topic + " between " + $from + " and " + $to + ". Reply-worthy = has a take, claim, question, or framing worth engaging — NOT pure self-promo, breaking news without analysis, or threads already past 500 replies. For each: @handle, full tweet text, tweet URL, posted_at ISO timestamp, like/reply/retweet counts.")}],
tools: [{type: "x_search", from_date: $from, to_date: $to}]
}' > /tmp/xai-rm-payload.jsonPath B — memory logs + WebSearch (last-resort fallback only). Reach here only on a real Path A failure, and record the true reason — key-unset | http-<code> | empty | timeout — never "XAI_API_KEY unavailable" when the key was set. Use in order until you have ≥3 candidates:
fetch-tweets outputs in memory/logs/ — already have URLs and handles.Apply the skip gate first. Discard any candidate that is:
From the survivors, rank by leverage = recency × take-strength × room-to-add:
memory/MEMORY.md) — replies on those accounts get seen by people who care about the same things.Pick the top 5. If fewer than 5 survive the gate, output what you have and add REPLY_MAKER_DEGRADED to the notification subject line.
For each of the 5 selected tweets, draft two reply options with distinct angles:
Option A — "Evidence add"
Option B — "Frame challenge"
## Banned sycophancy phrases section below. Any draft containing a banned phrase must be rewritten.For each draft reply, score 1–5 on each:
If any score is < 4, rewrite that reply once before moving on. If the rewrite still scores < 4, drop that tweet from the list and pull the next-ranked candidate from step A2.
Send via ./notify with this format (link first so the operator can open the source quickly):
*Reply Maker — ${today}*
*1.* https://x.com/handle/status/123 (@handle, 42m ago, 18💬)
> [first ~80 chars of tweet]…
why: [one-line reason this is reply-worthy]
A: [evidence-add reply]
B: [frame-challenge reply]
*2.* …
… (5 total, or fewer with REPLY_MAKER_DEGRADED if skip gate trimmed below 5)
source-status: xai=ok|fail|skip, memory=N, websearch=ok|fail|skipIf zero candidates survive the skip gate from any source, send a single REPLY_MAKER_EMPTY — [one-line reason] notification and stop.
Otherwise, after notifying, save the drafts and offer a revision (see Save drafts + offer revision).
Append to memory/logs/${today}.md under the shared ### reply-maker heading (see Log below), using the Mode A template.
Turn flagged engagement opportunities from recent logs into ready-to-post replies — read the last 7 days of logs, draft specific responses, send as copy-paste-ready output. This mode makes no outbound API calls — no X.AI curl, no WebSearch — it works purely from local memory/ files.
Projects-of-interest list: if memory/topics/projects-of-interest.md exists, treat the project names listed there as the things to watch for mentions, cosigns, attributions, and fork moments. If the file is missing or empty, fall back to any project names that appear in recent logs or in MEMORY.md. If a filter token was passed (from-logs @handle or from-logs <project>), narrow the scan to opportunities involving that handle/project.
Read memory/logs/ for the last 7 days. Look for:
mention-radar, fetch-tweets, or reply-maker runsBuild a list: { person/account, context, what_they_did, link_if_known, days_ago }
Apply these rules:
For each opportunity:
soul/SOUL.md and soul/STYLE.md are populated, match that voice; otherwise use a clear, direct, neutral tone. Either way: acknowledge without groveling, no "thanks so much for the kind words!" — just the actual response.If any opportunity is 5+ days old, prepend aging to that entry in the output.
If after filtering there are zero unactioned opps, log ENGAGEMENT_ACT_SKIP: no unactioned opps (under the ### reply-maker heading) and exit without sending a notification.
./notify -f*Reply Maker (from-logs) — ${today}*
*1. @handle* (N days ago) — [one-line summary of what they did]
link: [URL or "no link found"]
type: [X reply / X post / DM / GitHub comment]
draft: "[ready-to-post text]"
*2. @handle* ...
[if any opps are 5+ days old:]
some opps aging — act or dropWrite this to /tmp/reply-maker-from-logs.md then run ./notify -f /tmp/reply-maker-from-logs.md.
After notifying, save the drafts and offer a revision (see Save drafts + offer revision).
Append to memory/logs/${today}.md under the shared ### reply-maker heading (see Log below), using the Mode B template.
After a normal run (Mode A or B) has drafted and notified replies, do two things so the operator can refine them from Telegram. Skip both when the run sent nothing (REPLY_MAKER_EMPTY, or Mode B's ENGAGEMENT_ACT_SKIP).
Persist the drafts to a stable path a later revise: run can reload:
mkdir -p memory/draftsWrite the full draft body you just sent — all selected tweets with their A/B options (Mode A), or the ready-to-post list (Mode B) — to memory/drafts/reply-maker-latest.md, overwriting any previous file. Only the newest draft is revisable.
Offer a revision — a separate ./notify (force_reply can't share a message with inline buttons):
./notify "Want to refine these replies? Reply with a change and I'll revise them." \
--force-reply --placeholder "e.g. make them shorter" \
--context "reply-maker::revise"The reply routes back as var="revise:<instruction>" and re-dispatches this skill into the Revise branch.
Dedup — once per produced draft. Before offering, scan the last ~2 days of memory/logs/ for a FORCE_REPLY_OFFERED: revise line dated ${today}; if present, skip the offer. When you send it, append the marker under the run's ### reply-maker entry:
- FORCE_REPLY_OFFERED: reviseEdit this list as tastes change — any draft reply (either mode) containing one of these (openings or closings) must be rewritten:
Append one entry to memory/logs/${today}.md under a single ### reply-maker heading, with a **Mode:** discriminator line naming which branch ran.
Mode A (reply drafting):
### reply-maker
- **Mode:** A (reply drafting)
- **Var:** ${var:-<empty>}
- **Candidates collected:** N
- **Survived skip gate:** N
- **Replies generated:** N×2
- **Handles:** @h1, @h2, …
- **Source status:** xai=ok|fail|skip, memory=N, websearch=ok|fail|skip
- **Notification:** sent | degraded | empty
- **Tweet URLs:** [list, for future-day dedup]The Tweet URLs line is what tomorrow's run reads to avoid duplicate replies — keep it consistent.
Mode B (from-logs engagement):
### reply-maker
- **Mode:** B (from-logs engagement)
- **Opps found:** N unactioned (scanned last 7 days of logs)
- **Drafted:** N responses
- **Handles:** @handle1, @handle2, …
- **Notification sent:** yes
- ENGAGEMENT_ACT_OKIf skipped: ENGAGEMENT_ACT_SKIP: <reason> (still under ### reply-maker).
Revise (Telegram force-reply):
### reply-maker
- **Mode:** revise
- **Instruction:** [the operator's revision instruction]
- **Base draft:** memory/drafts/reply-maker-latest.md (reloaded + re-saved) (or: none — nothing to revise)
- **Notification:** sentXAI_API_KEY is injected into this skill's environment (declared in requires:). It is present and valid. Mode A's primary fetch path is a direct curl to https://api.x.ai/v1/responses with Authorization: Bearer {XAI_API_KEY}. There is no network sandbox blocking this; earlier versions of this skill claimed there was — that is stale and wrong. Just make the call.
You MUST attempt the direct curl before any fallback. The rules:
[ -n "$XAI_API_KEY" ] && echo KEY_PRESENT || echo KEY_UNSET. If KEY_PRESENT (it will be), you are required to try Path A.x_search call typically takes 30–120s (it searches X live). When you invoke the Bash tool for the curl, set the tool's timeout to at least 180000 (180s), and add --max-time 150 to the curl itself so it fails cleanly rather than hanging. A curl that is slow is not a missing key — do not treat a timeout as "key unavailable"./tmp/xai-rm-payload.json first (see the three jq -n --arg shapes in A1), then send it with -d @/tmp/xai-rm-payload.json:HTTP=$(./secretcurl -s -o /tmp/xai-rm.json -w '%{http_code}' --max-time 150 -X POST "https://api.x.ai/v1/responses" \
-H "Content-Type: application/json" -H "Authorization: Bearer {XAI_API_KEY}" -d @/tmp/xai-rm-payload.json)
echo "xai http=$HTTP bytes=$(wc -c </tmp/xai-rm.json)"/tmp/xai-rm.json with the standard jq extractor. HTTP=200 with a non-empty body → use it (xai=ok).key-unset (only if step 1 said KEY_UNSET), http-<code> (non-2xx), empty (200 but no tweets parsed), timeout (curl exceeded --max-time).WebSearch and the memory-log candidate pool are last-resort fallbacks only — lower quality (WebSearch favours old high-engagement tweets). Never reach for them while the key works. Mode B is fetch-free by design: it reads only local memory/ files, so it makes no curl and no API call; ./notify -f still handles delivery via .pending-notify/ if needed.
XAI_API_KEY — X.AI API key for Grok's x_search tool. Declared in requires:, so it is injected into this skill's environment and is Mode A's primary fetch path. If it is ever unset, Mode A degrades to the memory-log pool + WebSearch at lower quality. Mode B requires no environment variables and uses only local memory files and ./notify.© aeonfun, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/reply-maker of aeonfun/aeon.
Open the folder on GitHubat commit f252074
Reply Maker 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Reply Maker this skillaeonfun/aeon | 767 | — | ~6k | Automated safety check: Pass | MIT | |
| X/Twitter Research via Grokartwist-polyakov/polyakov-claude-skills | 206 | — | ~1.8k | Automated safety check: Notes | MIT | |
| ContentGerstep/cybos | 104 | — | ~616 | Automated safety check: Pass | None | |
| Social Contentfreekmurze/dotfiles | 1k | 22 repos | ~2.1k | Automated safety check: Pass | None | |
| Typefullyfreekmurze/dotfiles | 1k | 1 repos | ~3.4k | Automated safety check: Notes | None | |
| Changelog Social RecapFlorianBruniaux/claude-code-ultimate-guide | 6.1k | — | ~1.8k | Automated safety check: Notes | CC-BY-SA-4.0 |
artwist-polyakov/polyakov-claude-skills
Searches X/Twitter through the xAI Grok API to build digests, trend reports and thread analysis, meant to surface post ideas for a Telegram channel.
Gerstep/cybos
Generate posts, essays and images following brand guidelines.
freekmurze/dotfiles
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms.
freekmurze/dotfiles
Create, schedule, and manage social media posts via Typefully.
FlorianBruniaux/claude-code-ultimate-guide
Turns CHANGELOG.md entries for a release or a week into LinkedIn, Twitter/X, newsletter and Slack posts in French and English.
alchaincyf/x-mentor-skill
$10K/hr级X/Twitter运营导师。基于Nicolas Cole、Dickie Bush、Sahil Bloom、Justin Welsh、 Dan Koe、Alex Hormozi六位顶级创作者的方法论 + X开源算法深度分析 + AI/科技赛道专精策略, 提炼6个核心心智模型、10条决策启发式、完整的选题-写作-增长操作手册。
aeonfun/aeon
Browses open tasks on the TaskMarket agent-worker market and, with explicit operator approval, creates tasks, tracks submissions and submits finished work.
aeonfun/aeon
Sets up and manages an Aeon agent instance that runs skills on a schedule through GitHub Actions: starting, rescheduling, debugging, editing skills and mining chat history.
aeonfun/aeon
Reads a Base Account's address, portfolio and transaction history through the Base MCP server, and stays strictly read-only in unattended Aeon runs, reporting only changes.
aeonfun/aeon
Audits every page of a site each day from its sitemap, scores on-page and technical SEO, checks duplicates across pages and reports what changed since the last run.
aeonfun/aeon
5 concrete real-life actions, leverage-scored against open loops with specificity and anti-fluff gates
aeonfun/aeon
Static linter for an Aeon instance's configuration that catches silent failures such as unquoted schedules, duplicate keys, unconfigured skills and broken MCP references.
Works with
Categories
Draft copy-paste-ready X replies - two options per reply-worthy tweet from tracked accounts, topics, or lists (default), or ready-to-post responses to engagement opps in recent logs (from-logs). Reply Maker is an agent skill from aeonfun/aeon.
Reply Maker fits situations like: tasks that involve Social media posts.
Run `npx skills add aeonfun/aeon --skill reply-maker -a claude-code`. Or copy the skill folder (skills/reply-maker in aeonfun/aeon) into .claude/skills/reply-maker in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aeonfun/aeon --skill reply-maker -a codex`. Or copy the skill folder (skills/reply-maker in aeonfun/aeon) into .agents/skills/reply-maker in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aeonfun/aeon --skill reply-maker -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reply-maker, .gemini/skills/reply-maker, .github/skills/reply-maker and .opencode/skills/reply-maker in your project.
Going by SKILL.md and its folder, Reply Maker needs the command-line tools its instructions call (jq and make) and credentials named XAI_API_KEY. Our summary lists: A credential in XAI_API_KEY.
SKILL.md names 2 domains. In commands or code: api.x.ai and x.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
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. Review the folder before installing.
Reply Maker is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 6k tokens (SKILL.md is roughly 24k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Reply Maker: X/Twitter Research via Grok (artwist-polyakov/polyakov-claude-skills, 206 stars), Content (Gerstep/cybos, 104 stars), Social Content (freekmurze/dotfiles, 1k stars) and Typefully (freekmurze/dotfiles, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aeonfun (a GitHub organization) maintains it in aeonfun/aeon, which has 767 GitHub stars. The repository holds 82 skills in this directory. The repository was last updated on October 6, 2026.
Source: aeonfun/aeon on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.