Agent Skillsaaronjmars/aeon › Reply Maker

Reply Maker

GitHub

用于起草可直接复制的X平台回复。支持模式A:基于兴趣或指定范围自动发现并生成两条回复选项;模式B:扫描日志中的互动机会生成即时回复;以及修订分支:根据指令优化已生成的回复内容。

skills/reply-maker/SKILL.md aaronjmars/aeon

Trigger Scenarios

用户需要为推文撰写回复草稿 用户希望基于特定账号、列表或话题生成回复 用户需要从日志中提取互动机会并生成回复 用户要求修改或优化之前生成的回复

Install

npx skills add aaronjmars/aeon --skill Reply Maker -g -y
More Options

Use without installing

npx skills use aaronjmars/aeon@Reply Maker

指定 Agent (Claude Code)

npx skills add aaronjmars/aeon --skill Reply Maker -a claude-code -g -y

安装 repo 全部 skill

npx skills add aaronjmars/aeon --all -g -y

预览 repo 内 skill

npx skills add aaronjmars/aeon --list

SKILL.md

Frontmatter
{
    "var": "empty = auto-discover reply-worthy tweets and draft two options each; @handle \/ numeric X list ID \/ topic = scope the drafting to that; from-logs (or --from-logs [@handle|project]) = turn flagged engagement opps from recent logs into ready-to-post replies",
    "name": "Reply Maker",
    "tags": [
        "social",
        "meta"
    ],
    "type": "Skill",
    "commits": false,
    "category": "social",
    "requires": [
        "XAI_API_KEY?"
    ],
    "description": "Draft copy-paste-ready X replies — either two reply options per reply-worthy tweet from tracked accounts\/topics\/lists (default), or (from-logs mode) ready-to-post responses to engagement opportunities flagged in recent logs",
    "permissions": []
}

${var} — selects the mode and scope:

  • emptyMode 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 / topicMode A (Reply Drafting) scoped to that handle, list, or topic.
  • from-logs (or --from-logs, optionally followed by an @handle or 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).

Preamble (both modes)

Read memory/MEMORY.md for context on active projects and open engagement follow-ups.

Then read memory/logs/ — the window depends on the mode:

  • Mode A: the last 2 days of memory/logs/ for recent list-digest, tweet-roundup, and prior reply-maker outputs (used as a candidate pool and for reply de-duplication).
  • Mode B: the last 7 days of memory/logs/ for engagement opportunities flagged by other skills (project-pulse, refresh-x, reply-maker, channel-recap) or noted in MEMORY.md "Known Follow-ups".

Parse ${var} to pick the branch (trim whitespace, compare case-insensitively):

  • If ${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.
  • If ${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.
  • Otherwise run Mode A (Reply Drafting), treating ${var} as the scope: empty, @handle, numeric X list ID, or a topic string.

Voice

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:

  • Direct and substantive — no fluff, no sycophancy
  • Under 280 characters each (X replies; DMs and GitHub comments may run longer — see Mode B)
  • Opinionated but grounded in specifics
  • The kind of reply that adds to the conversation, not noise

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 branch (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:

  1. Strip the prefix. The instruction is ${var#revise:} (keep any inner colons). Trim whitespace — e.g. make them shorter, less formal, drop reply B on #2.
  2. Load the last draft. Read memory/drafts/reply-maker-latest.md — the stable path every normal run saves to (see the save steps in A4 / B6). If it's missing or empty, there's nothing to refine: send ./notify "Nothing to revise yet — run reply-maker first, then reply here to refine the drafts." and end the run.
  3. Apply the instruction. Read soul/ for voice, then regenerate the saved replies applying the operator's instruction. Keep the same set of target tweets and the same A/B two-option structure (Mode A) or ready-to-post list (Mode B) — you're refining wording, not re-discovering candidates. Re-enforce the hard reply rules: ≤280 chars for X replies, no sycophancy (see Banned sycophancy phrases), specifics not gestures.
  4. Re-save the revised drafts to memory/drafts/reply-maker-latest.md (overwrite), so a further revise: refines the newest version.
  5. Re-send via ./notify in the same format the originating mode uses, with a first line flagging it as a revision, e.g. revised (${var#revise:}):. Use ./notify -f <file> for multi-line output.
  6. Re-offer a further revision (the operator is actively iterating, so this is expected, not a nag — skip the daily dedup guard here):
    ./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"
    
  7. Log under ### reply-maker with - **Mode:** revise and the instruction (see Log), then end the run — do NOT run Mode A or B.

Mode A — Reply Drafting

Generate two reply options for 5 reply-worthy tweets from tracked X accounts, a list, or a topic.

A1. Gather candidate tweets

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 — pre-fetched cache (preferred). The workflow pre-fetches Grok x_search results to .xai-cache/reply-maker.json (via scripts/prefetch-xai.sh, which has full env access and runs outside the Claude sandbox). Read it first:

jq -r '.output[] | select(.type == "message") | .content[] | select(.type == "output_text") | .text' .xai-cache/reply-maker.json

If parsing yields candidates, use them. The prefetch script already shapes the request based on ${var} (numeric list ID, @handle, or topic) — see "Strategy depends on ${var}" below for the contract it implements.

Path B — direct curl: Skipped. The sandbox blocks env-var-authenticated curl; do not attempt at runtime.

Strategy depends on ${var}:

If ${var} looks like an X list ID (numeric):

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)
LIST_ID="${var}"

curl -s -X POST "https://api.x.ai/v1/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $XAI_API_KEY" \
  -d '{
    "model": "grok-4-1-fast",
    "input": [{"role": "user", "content": "Look at X list https://x.com/i/lists/'"$LIST_ID"'. Return the 12 most reply-worthy original posts (not retweets, not replies) by members of this list between '"$FROM_DATE"' and '"$TO_DATE"'. 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": "'"$FROM_DATE"'", "to_date": "'"$TO_DATE"'"}]
  }'

If ${var} looks like a @handle: same call, scoped to that handle's recent original posts.

If ${var} is a topic (or empty): same call with ${var} (or top 2–3 topics from memory/MEMORY.md) as the search query. When empty, also pull tweet candidates surfaced in the last 2 days of tweet-roundup and list-digest logs as a backup pool.

Fallback chain (use in order until you have ≥3 candidates):

  1. Pre-fetched XAI cache at .xai-cache/reply-maker.json (Path A above)
  2. Recent list-digest + tweet-roundup outputs in memory/logs/ — already have URLs and handles
  3. WebSearch for very recent posts on memory topics (filter: posted within last 6h, original post not reply)

The memory logs are the most reliable source since they're already fetched — prefer them over retrying a blocked API.

A2. Filter and select 5 tweets

Apply the skip gate first. Discard any candidate that is:

  • Pure self-promo (launching a product, "buy my course", subscribe links)
  • Breaking-news repost without an angle of its own
  • A thread already past ~500 replies (your reply will not be seen)
  • Older than 6 hours (reply window has closed; don't waste a reply slot)
  • A handle/URL already replied to in the last 7 days of reply-maker logs (no duplicates)

From the survivors, rank by leverage = recency × take-strength × room-to-add:

  • Recency: minutes-ago > hours-ago. Tweets <60min old are top priority.
  • Take-strength: a clear claim/question/framing you can either reinforce with evidence or challenge with a flipped premise.
  • Room-to-add: not already swarmed; thread isn't full of stronger replies; you have actual context to contribute.
  • Bias toward authors whose audience overlaps your interests (from 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.

A3. Generate two replies per tweet

For each of the 5 selected tweets, draft two reply options with distinct angles:

Option A — "Evidence add"

  • Builds on their point with a specific datum, named project, named person, concrete number, link, or counterexample they didn't include
  • Tone: collaborative, substantive, calmly confident
  • Must contain at least one named entity, number, or specific reference — vague "great insight, here's another angle" is banned

Option B — "Frame challenge"

  • States the premise you're pushing back on explicitly (one short clause), then offers the contrarian angle, flipped framing, or sharper read
  • Tone: direct, opinionated, not contrarian-for-its-own-sake
  • Must contain the actual disagreement, not a hedge — vague "interesting, but have you considered..." is banned

Hard reply rules (apply to both A and B)

  • ≤ 280 characters including any handle prefix
  • No sycophancy — see the ## Banned sycophancy phrases section below. Any draft containing a banned phrase must be rewritten.
  • No hedging stacks — "It could be argued that…", "Just my two cents but…", "Maybe I'm wrong but…" — pick a position
  • Specifics, not gestures — names, projects, numbers, links. If you can't cite one, don't write the reply
  • Stand alone — readers may not see the original tweet; reply must make sense on its own
  • Match soul voice if soul files are populated

Self-edit pass (do this for every reply before finalizing)

For each draft reply, score 1–5 on each:

  • Specific: cites a name/number/project/claim?
  • Standalone: makes sense without reading the parent?
  • Non-sycophantic: passes the banned-phrase list?
  • Voice-matched: sounds like the soul files (or neutral-direct if no soul)?

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.

A4. Notify

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|skip

If 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).

A5. Log

Append to memory/logs/${today}.md under the shared ### reply-maker heading (see Log below), using the Mode A template.


Mode B — From-Logs Engagement

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 and ignores the .xai-cache/reply-maker.json prefetch — 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.

B1. Collect unactioned engagement opportunities

Read memory/logs/ for the last 7 days. Look for:

  • Log entries flagging engagement opps (e.g. "Engagement opps: N flagged" with N > 0) — extract the named handles/accounts
  • Any person who cosigned, mentioned, or attributed one of the operator's projects-of-interest
  • GitHub attribution or fork moments not yet acknowledged
  • Entries in MEMORY.md "Known Follow-ups" explicitly flagging engagement opps
  • Cosigns or mentions surfaced in refresh-x, reply-maker, or channel-recap runs

Build a list: { person/account, context, what_they_did, link_if_known, days_ago }

B2. Filter and prioritize

Apply these rules:

  • Drop any opp older than 14 days — window is likely closed
  • De-dupe: skip opps where recent logs already show "replied to @X" or "acknowledged" for that handle
  • Rank by: recency (fresher first) × leverage (high-follower or influential account first)
  • Cap at 5 opportunities

B3. Draft ready-to-post responses

For each opportunity:

  • Type: X reply / X DM / GitHub comment / X post
  • Target: @handle or URL
  • Draft text: exact text, ready to copy-paste
  • Keep under 280 chars for X replies; longer is fine for DMs or GitHub comments
  • Voice: if 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.

B4. Check for staleness

If any opportunity is 5+ days old, prepend aging to that entry in the output.

B5. Skip if empty

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.

B6. Write output to a temp file, then send via ./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 drop

Write 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).

B7. Log

Append to memory/logs/${today}.md under the shared ### reply-maker heading (see Log below), using the Mode B template.


Save drafts + offer revision (both modes)

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).

  1. Persist the drafts to a stable path a later revise: run can reload:

    mkdir -p memory/drafts
    

    Write 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.

  2. 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: revise
    

Banned sycophancy phrases

Edit this list as tastes change — any draft reply (either mode) containing one of these (openings or closings) must be rewritten:

  • Openings: "Great point", "Love this", "100%", "This 👆", "Couldn't agree more", "So well said", "💯"
  • Closings: "Curious to hear your thoughts!" (engagement-hook noise)

Log

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_OK

If 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:** sent

Sandbox note

  • Mode A: the sandbox blocks outbound curl with $XAI_API_KEY in headers — always read the pre-fetched .xai-cache/reply-maker.json (populated by scripts/prefetch-xai.sh) or fall through to the memory/WebSearch fallback chain. Do not attempt direct curl to api.x.ai at runtime. Use WebFetch for any non-auth URL fetches.
  • Mode B: reads only local memory/ files. No outbound network calls needed — no curl, no API. ./notify -f handles delivery reliably even when the sandbox blocks curl (it writes to .pending-notify/ as a fallback).

Environment Variables Required

  • XAI_API_KEY — X.AI API key for Grok x_search (Mode A only, optional — falls back to WebSearch + memory logs). Mode B requires no environment variables and uses only built-in memory files and ./notify.

Version History

  • fb16753 Current 2026-07-05 12:07

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Metadata

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Version
fb16753
Hash
a8734e53
Indexed
2026-07-05 12:07

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