Claude
3027bb0400
Light up the moderation dashboard's previously-empty widgets by persisting the
event streams the bot only reacted to in-memory before.
Schema (bot-owned)
- member_events: join/leave, with invite_code/inviter_* for best-effort invite
attribution on joins
- filter_hits: word / foreign-invite filter deletions (matched + action_taken)
- spam_hits: rate_limit / mass_mention / mass_emoji detections
Bot
- new models memberEvents/filterHits/spamHits
- guildMemberAdd records the join with invite attribution; new inviteTracker.js
keeps an invite-use cache (GuildInvites intent + inviteCreate/inviteDelete) and
diffs it on join to find which invite was used — best-effort, never blocks
auto-role
- new guildMemberRemove records leaves
- messageFilter records filter/spam hits alongside the existing warn/mute;
inviteFilter now returns the offending code; detectSpam identifies which spam
rule tripped (preserving the rate-limit-first side-effect order)
- mod_actions still logs the resulting warn/mute — the new tables are additive
Server
- summary extended with joins/leaves/invite_joins/filter_hits/spam_hits per window
- new feeds: /api/v1/admin/moderation/{members,filter-hits,spam-hits}
Client
- overview now shows 8 tiles (mod actions + joins/leaves/filter/spam, joins tile
notes "N via invite") plus an Events panel with Members/Filter/Spam tabs;
removed the coming-soon note
Verified: 119 server unit tests, client build, 14-check DB-backed smoke, and a
browser click-through of every tile and events tab (incl. invite attribution).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019rao86n5cXpwAyjdBFEshV
48 lines
1.7 KiB
JavaScript
48 lines
1.7 KiB
JavaScript
// Pure reshaping/annotation helpers for the moderation dashboard, deliberately
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// free of any DB (or other side-effecting) imports so they can be unit-tested
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// without opening a database pool. moderation.model re-exports these.
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function zeroCounts() {
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return { ban: 0, kick: 0, mute: 0, warn: 0 }
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}
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// Tag each action as automated (staff is the bot) and fold the joined
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// user_identities columns into a linked_account object. The string coercion
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// matters — snowflakes can arrive as number or string from different columns.
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function annotate(rows, appId) {
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return rows.map((r) => {
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const isAutomated = appId != null && String(r.staff_user_id) === String(appId)
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return {
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...r,
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is_automated: isAutomated,
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linked_account: r.target_site_user_id
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? { id: r.target_site_user_id, username: r.target_site_username }
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: null,
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}
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})
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}
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// Fold the per-type window rows into the { windows: { '24h', '7d', '30d' } }
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// shape the dashboard tiles consume, zero-filling any type with no rows.
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function reshapeWindows(rows) {
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const windows = { '24h': zeroCounts(), '7d': zeroCounts(), '30d': zeroCounts() }
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for (const row of rows) {
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const t = row.action_type
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if (windows['24h'][t] === undefined) continue
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windows['24h'][t] = Number(row.d1) || 0
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windows['7d'][t] = Number(row.d7) || 0
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windows['30d'][t] = Number(row.d30) || 0
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}
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return { windows }
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}
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// Pull the count for one window key ('24h'|'7d'|'30d') out of a
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// { d1, d7, d30 } sum row, coercing to a number and tolerating a null row.
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function windowValue(row, key) {
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if (!row) return 0
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const col = key === '24h' ? row.d1 : key === '7d' ? row.d7 : row.d30
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return Number(col) || 0
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}
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module.exports = { zeroCounts, annotate, reshapeWindows, windowValue }
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