本文へ移動
cccskills
無料GitHub で公開

annotations-refresh

Drain the chart-annotation candidate queue into reviewed per-coin annotations. Use weekly during active event periods, monthly otherwise, or when queue-health checks warn.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md6.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Read docs/editorial-style.md; its technical-evidence register governs prose.

Annotation Refresh

npm run candidates:annotations writes machine-found events to ignored agents/annotation-candidates.{md,json}. Editorially classify each row as promote, drop, or defer; never auto-publish a producer signal.

This is permanent editorial intake, not a pending chart feature. The live chart overlay is retired; keep the curated corpus, review decisions, deferrals, legacy backup, and downloaded snapshots. A reviewed corpus edit does not restore the overlay or authorize automatic publication. Hosted artifacts expire, so retain the reviewer handoff separately.

Use npm run research:dwellir-rpc -- for supplemental pinned on-chain evidence reads; see docs/process/agent-artifacts.md#pinned-on-chain-evidence. Cite its provenance record (keyless URL, block, timestamp); never cite latest reads as evidence.

Recover The Backlog

Scheduled runs retain full immutable agent-maintenance-candidates-<run-id>-<attempt> artifacts for 90 days, covering monthly review plus a missed monthly review. The issue contains excerpts and a download link, not the complete backlog. Before a sweep, download all retained runs since the last handoff (include failed runs with partial artifacts). From the repository root, with GitHub read access:

set -o pipefail
history_dir=agents/annotation-history
mkdir -p "$history_dir"
since_date=$(node -e 'process.stdout.write(new Date(Date.now() - 90 * 86400000).toISOString().slice(0, 10))')
gh api --paginate -X GET 'repos/{owner}/{repo}/actions/workflows/agent-maintenance-candidates.yml/runs' \
  -f created=">=$since_date" -f status=completed -f per_page=100 --jq '.workflow_runs[].id' |
  while read -r run_id; do
    gh run download "$run_id" --pattern 'agent-maintenance-candidates-*' --dir "$history_dir/$run_id" || exit 1
  done
npm run candidates:annotations -- --replay "$history_dir"

Use a shell with pipefail enabled so a failed run listing does not look like an empty history. Download failures, expired runs, or runs without artifacts are coverage gaps to resolve/report; do not silently skip them. Existing local download directories can be reused for replay without redownloading. --replay is offline: it merges every annotation-candidates.json under that directory with the local queue, preserving legacy rows and deferrals. It never writes decisions or product annotations. Keep agents/annotation-review.json, the queue, and needed snapshots together in the review handoff; do not delete them merely because the scheduled issue changed.

On the first migration of a legacy Markdown queue, the producer preserves its exact original bytes as agents/annotation-candidates.legacy.md and links it from the new queue. Read that backup for indented deferral evidence, source gaps, and free-form review notes the row parser cannot interpret. Keep it in the handoff too; it is never overwritten automatically.

Live collection overlaps 14 days of tape history and follows cursors serially with page/deadline bounds. JSON coverage and queue source notes distinguish complete from incomplete collection windows. Missing pages/sources remain pending evidence even when the command succeeds. Review dispositions identify individual events; a complete collection window is not a completed editorial review. The legacy date-only last_swept_at comment is preserved for compatibility and no longer suppresses arrivals or advances automatically.

Review

  1. Read the recovered queue oldest-first, its source coverage and existing annotation-review.json, shared/types/chart-annotation.ts, shared/data/annotations/curated-annotations.ts, and each referenced shared/data/annotations/coins/<id>.json. Source files own shape, enum, severity, and validation. Match distinct same-day events by their printed id, not just date/coin/kind.
  2. Promote only a discrete event supported by a primary source (issuer post-mortem, regulator filing, methodology changelog, transaction/on-chain proof) and not already represented within the same incident window. Secondary reporting may corroborate, not replace missing primary evidence.
  3. Drop duplicates, low-signal/promotional items, unsupported chatter, and announcements without a live transition. Defer real events whose decisive source is not yet available; include the reason.
  4. A producer launch hint is not an annotation enum. Use an established curated kind only when primary-source evidence supports that classification; do not invent a new kind or require the retired chart overlay to exist.

Apply

For promoted rows, add { date, kind, label, severity?, href?, note? } to the per-coin JSON in ascending date order. Keep labels within the source limit and put rationale in note. Create/register a new coin file only when needed, following the loader’s existing pattern.

Record each decision by the exact printed row id in reviewer-owned agents/annotation-review.json (create it on the first review). The schema is exported as AnnotationReviewSchema by scripts/maintenance/build-annotation-candidates.ts:

{
  "version": 1,
  "decisions": {
    "tape:example-event-id": {
      "disposition": "defer",
      "reviewedAt": "2026-09-07T12:00:00.000Z",
      "reason": "Await issuer post-mortem; revisit when published"
    }
  }
}

Use promote, drop, or defer; promoted rows must have their annotation edit applied before recording promotion. Keep promoted/dropped IDs to prevent replay from requeuing them, and retain a reason/trigger for deferrals. Preserve legacy row IDs on migration. Rerun the offline replay command after decisions: it removes promoted/dropped rows from the Markdown view, retains deferrals, and admits new same-day IDs. Do not advance last_swept_at or manufacture a reviewed interval from incomplete collection. Record promote/drop/defer counts in the closeout.

Validate:

npm run check:stablecoin-data
npm test -- curated-annotations

Report promoted counts by coin, drop reasons, each deferral trigger, remaining rows/oldest date, and checks. Never invent dates, collapse distinct multi-day events, or treat a producer signal as its own evidence.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Generate a weekly changelog entry from git history, filtering operational noise and producing editorial summary, field notes, statistics, and a bounded commit manifest. Stops for review unless commit was explicitly requested.

日本語の概要は準備中です。原文の説明を表示しています。

TokenBrice/pharos-watch232026年10月10日 更新

Research and populate tracked stablecoin compliance sidecars for the U.S. GENIUS Act, EU MiCA, or both. Use when adding or auditing authorization, applicability, pathway, or disclosure evidence.

日本語の概要は準備中です。原文の説明を表示しています。

TokenBrice/pharos-watch232026年10月10日 更新

Use when adding, reviewing, squashing, deploying, or rolling back Pharos D1 migrations or schema cleanup.

日本語の概要は準備中です。原文の説明を表示しています。

TokenBrice/pharos-watch232026年10月10日 更新

Drain the Pharos Dependency Map coverage-audit queues into evidence-refreshed edges, reviewed target dispositions, or documented deferrals. Use monthly after weekly production dependency audits, after dependency coverage drops, or when reviewing adapter gaps, material unlinked slices, symbol leads, duplicate/split groups, or unverifiable published edges.

日本語の概要は準備中です。原文の説明を表示しています。

TokenBrice/pharos-watch232026年10月10日 更新

Update Pharos funding donations by reconciling inbound transfers, rejecting wallet self-activity and spam, pricing receipt-time value, and appending user-approved rows.

日本語の概要は準備中です。原文の説明を表示しています。

TokenBrice/pharos-watch232026年10月10日 更新

Draft a short, prioritized questionnaire for a collaborating stablecoin team when public evidence cannot resolve important Pharos data or confidence gaps.

日本語の概要は準備中です。原文の説明を表示しています。

TokenBrice/pharos-watch232026年10月10日 更新

TokenBrice のスキルをすべて見る

このスキルの問題を報告する