Agent Skillsaeonfun/aeon › Mention Radar

Mention Radar

GitHub

监控外部网络及社交媒体上关于活跃项目的提及,识别用户发现、困惑或摩擦点。通过X.AI API和WebSearch搜索最近7天数据,排除操作者自身内容,优先展示首次发现、疑问或竞品对比的讨论,便于及时互动。

skills/mention-radar/SKILL.md aeonfun/aeon

触发场景

用户希望了解项目的外部口碑和用户反馈 需要监控特定项目在社交媒体上的曝光和讨论情况 寻找潜在的用户支持机会或产品改进建议

安装

npx skills add aeonfun/aeon --skill Mention Radar -g -y
更多选项

不安装直接使用

npx skills use aeonfun/aeon@Mention Radar

指定 Agent (Claude Code)

npx skills add aeonfun/aeon --skill Mention Radar -a claude-code -g -y

安装 repo 全部 skill

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

预览 repo 内 skill

npx skills add aeonfun/aeon --list

SKILL.md

Frontmatter
{
    "var": "",
    "name": "Mention Radar",
    "tags": [
        "social",
        "dev"
    ],
    "type": "Skill",
    "commits": false,
    "category": "productivity",
    "requires": [
        "XAI_API_KEY?"
    ],
    "schedule": "25 7 2\/2 * *",
    "description": "Monitor external web and social mentions of the operator's active projects - surface what people are discovering, where they're confused, and where to engage",
    "permissions": []
}

${var} — Comma-separated project names to track (e.g. "MyApp, my-lib"). If empty, derives targets from MEMORY.md and memory/topics/projects.md.

Read memory/MEMORY.md for current project status. Read the last 3 days of memory/logs/ to avoid re-surfacing already-noted mentions.

Steps

  1. Define the targets.

    • If ${var} is set: parse it as a comma-separated list of project names.
    • Otherwise: scan memory/MEMORY.md (goals, active topics) and memory/topics/projects.md (if it exists) for the operator's active projects. A target needs at least a name; collect a site/domain and a GitHub owner/repo too when known.
    • Cap at 6 targets — prefer the most active ones.
    • If zero targets can be derived: log MENTION_RADAR_SKIP: no projects configured — set var or add projects to memory/topics/projects.md and stop. No notification.

    For each target, build search terms:

    • The exact project name in quotes (e.g. "MyApp" site:x.com OR site:reddit.com OR site:news.ycombinator.com)
    • The domain if known (e.g. "myapp.xyz")
    • The repo if known (e.g. site:github.com owner/myapp)
  2. Search for external mentions. X/Twitter is fetched via the X.AI Responses API (primary); the rest of the public web (Reddit, Farcaster, blogs, newsletters, GitHub Discussions, HN, Product Hunt) goes through WebSearch, which is also the last-resort fallback for X itself. Derive the operator's handle from soul/SOUL.md if present (call it $OPERATOR) so you can exclude their own posts.

    Path A — X.AI API (primary, X/Twitter mentions). For each target, ask Grok's x_search who is talking about the project on X. See the Fetching contract below — attempt this whenever the key is present, set the Bash tool timeout to ≥180000, and capture the HTTP status. Use a unique tmp filename per target if you loop (e.g. /tmp/xai-mr-$SLUG.json). $NAME/$DOMAIN/$REPO come from the target built in step 1 ($DOMAIN/$REPO may be empty — leave them out if so):

    FROM_DATE=$(date -u -d "7 days ago" +%Y-%m-%d 2>/dev/null || date -u -v-7d +%Y-%m-%d)
    TO_DATE=$(date -u +%Y-%m-%d)
    PROMPT="Search X for posts by OTHER people mentioning the project \"${NAME}\" (also its site ${DOMAIN} and repo ${REPO} when given), posted between ${FROM_DATE} and ${TO_DATE}. Exclude posts by the operator @${OPERATOR} and by the project's own accounts. For each mention return: @handle, the full post text, date, exact engagement counts (likes, retweets, replies; 0 if unknown), the poster's approximate follower count if visible, and the direct link https://x.com/handle/status/ID. Prioritize people discovering it for the first time, asking confused questions, hitting friction (setup/docs/missing feature), comparing it to a competitor, or requesting a feature. Return a numbered list; if nobody is talking about it, say so explicitly."
    jq -n --arg p "$PROMPT" --arg fd "$FROM_DATE" --arg td "$TO_DATE" \
      '{model:"grok-4.3", input:[{role:"user",content:$p}], tools:[{type:"x_search",from_date:$fd,to_date:$td}]}' \
      > /tmp/xai-mr-payload.json
    HTTP=$(./secretcurl -s -o /tmp/xai-mr.json -w '%{http_code}' --max-time 150 -X POST "https://api.x.ai/v1/responses" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer {XAI_API_KEY}" \
      -d @/tmp/xai-mr-payload.json)
    echo "xai http=$HTTP bytes=$(wc -c </tmp/xai-mr.json)"
    

    On HTTP=200 with a non-empty body, parse /tmp/xai-mr.json with jq -r '.output[] | select(.type == "message") | .content[] | select(.type == "output_text") | .text' and feed the X mentions into categorization (step 4). Record X_SOURCE=api.

    Path B — WebSearch (broader web + X fallback). Always use WebSearch for the non-X surfaces — Reddit, Farcaster, personal blogs, newsletters, GitHub Discussions, HN, Product Hunt:

    • Try both brand name and URL variants
    • Time-box to last 7 days where the search engine supports it
    • Skip results from the operator's own accounts and the project's own repos

    WebSearch is also the fallback for X/Twitter, but only when Path A truly failed (key-unset, http-<code>, empty, or timeout — record the real reason per the Fetching contract, never "XAI_API_KEY unavailable" when the key was set). On the X fallback query site:x.com "<project name>" after:${FROM_DATE}; note in the log that X results came from WebSearch (lower quality) and set X_SOURCE=websearch.

  3. Also check GitHub network signals for each target with a known repo:

    gh api repos/OWNER/REPO --jq '{stars: .stargazers_count, forks: .forks_count, watchers: .watchers_count}'
    

    Skip any repo that 404s (private or not yet public). Compare to the last log entry to compute deltas. If no prior data, record as baseline.

  4. Categorize each mention found:

    • Discovery — person found the project for the first time, sharing it, impressed ("this is cool", star notification, share)
    • Confusion — person unclear on what it does, asking questions, mischaracterizing it
    • Friction — person ran into a problem (setup, docs, missing feature)
    • Competitor comparison — mentioned alongside or against a competing project
    • Feature request / wish — explicit ask for something missing
    • Press / newsletter — cited in a publication or digest
  5. Identify engagement opportunities. Flag any mention where:

    • The person is confused and a 1-tweet clarification would help
    • A feature request aligns with what's being built
    • A competitor comparison is wrong or incomplete
    • A high-follower account discovered the project (high-leverage reply opportunity)
  6. Format the output (under 4000 chars):

    *Mention Radar — ${today}*
    
    {PROJECT NAME, uppercased}
    - [source] — [what they said] — [category]
    ...
    (one section per target)
    
    ENGAGEMENT OPPORTUNITIES
    - [handle/source]: [why worth replying]
    
    QUIET: [project] — no external mentions found
    

    Use QUIET: [project] for any project with zero external mentions this cycle. Skip GitHub-only star delta if it's less than 5 — only mention notable jumps.

  7. Only notify if there's signal. Skip notification if ALL projects are quiet and no GitHub deltas > 5 stars. Log MENTION_RADAR_QUIET instead.

  8. Send via ./notify if there's anything worth surfacing.

  9. Log to memory/logs/${today}.md:

    ### mention-radar
    - **{project}:** [N mentions / QUIET]
    (one line per target)
    - **Top find:** [best mention in one line, or "none"]
    - **Engagement opps:** [N flagged, or 0]
    - **Notification sent:** yes/no
    

Guidelines

  • This is signal filtering, not a metrics report. One real conversation > ten impressions.
  • Prioritize quality of mention over quantity. A thoughtful Reddit post or HN comment matters more than a retweet.
  • Don't manufacture urgency. If there's nothing worth acting on, say so.
  • Be specific — link the source, quote the key line, name the person if identifiable.
  • The point is engagement opportunity and awareness, not vanity numbers.

Fetching

XAI_API_KEY is injected into your environment for this skill (declared in requires:). It is present and valid. The primary fetch path for X/Twitter mentions is a direct curl to https://api.x.ai/v1/responses with Authorization: Bearer {XAI_API_KEY} (step 2, Path A). 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 X fallback. The rules:

  1. Check, don't assume. Run [ -n "$XAI_API_KEY" ] && echo KEY_PRESENT || echo KEY_UNSET. If KEY_PRESENT (it will be), you are required to try Path A.
  2. Allow enough time. The 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 keep --max-time 150 on 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".
  3. Capture the HTTP status so the fallback decision is based on fact, not assumption. Build the payload to the fixed file /tmp/xai-mr-payload.json first (the jq -n --arg in Path A), then send it with -d @file — the ./secretcurl command must stay 100% literal (no $VAR):
    HTTP=$(./secretcurl -s -o /tmp/xai-mr.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-mr-payload.json)
    echo "xai http=$HTTP bytes=$(wc -c </tmp/xai-mr.json)"
    
    Then parse /tmp/xai-mr.json with the standard jq extractor. HTTP=200 with a non-empty body → use it (X_SOURCE=api).
  4. Fall back only on a real failure, and record the true reason — never write "XAI_API_KEY unavailable" when the key was set. Use one of: key-unset (only if step 1 said KEY_UNSET), http-<code> (non-2xx), empty (200 but no mentions parsed), timeout (curl exceeded --max-time).

WebSearch / WebFetch are last-resort fallbacks only for X — lower quality (WebSearch favours old high-engagement tweets). They remain the primary tool for the non-X web surfaces (Reddit, HN, blogs, etc.). Never reach for the X WebSearch fallback while the key works.

Environment Variables

  • XAI_API_KEY — X.AI API key for Grok's x_search tool. Declared in requires: (optional ?), so it is injected into this skill's environment and is the primary path for X/Twitter mentions. If it is ever unset, X mentions degrade to the WebSearch fallback at lower quality; the broader-web search is unaffected.
  • gh CLI — pre-authenticated in GitHub Actions; used for the GitHub network-signal check (step 3). Not an env var you set here.

版本历史

  • ed82d8a 当前 2026-07-31 03:01
  • d96f176 2026-07-19 14:09

    更新底层模型配置,将废弃的x_search模型迁移至grok-4.3以兼容xAI最新API规范;同时支持Grok 4.5并优化相关构建工具链配置。

  • fb16753 2026-07-05 12:07

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元信息

文件数
0
版本
bb1cfc3
Hash
ecfc746b
收录时间
2026-07-05 12:07

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