fix(recall): use upvote time for confidence recency (#1278)

docs/guide/knowledge.md

@@ -99,7 +99,7 @@ teamai recall maintenance --update-quality
 
 `--archive` puts aside learnings whose confidence is below 0.15. `--update-quality` writes a `.draft.md`. Rename it to `.md` when the draft is right.
 
-Confidence is an activity score from 0 to 1, not a probability that the knowledge is correct or a task succeeded. Its upvote-to-recall ratio is capped at 1, so repeated positive feedback cannot exceed that factor's 30% weight or replace the recency factor.
+Confidence is an activity score from 0 to 1, not a probability that the knowledge is correct or a task succeeded. Its upvote-to-recall ratio is capped at 1, so repeated positive feedback cannot exceed that factor's 30% weight. Recency uses the later of the last recall and the last upvote, so a fresh upvote also refreshes recency.
 
 ### Promoting Learnings
 

docs/guide/zh-CN/knowledge.md

@@ -99,7 +99,7 @@ teamai recall maintenance --update-quality
 
 `--archive` 收走置信度低于 0.15 的 learning。`--update-quality` 写出 `.draft.md`，改好后把文件名改成 `.md`。
 
-置信度是 0 到 1 的活动评分，不是知识正确或任务成功的概率。正反馈计数与召回计数的比值最高按 1 计算，因此重复正反馈不会超出这一项 30% 的权重，也不能代替近期召回这一项。
+置信度是 0 到 1 的活动评分，不是知识正确或任务成功的概率。正反馈计数与召回计数的比值最高按 1 计算，因此重复正反馈不会超出这一项 30% 的权重。近期度取最近一次召回与最近一次正反馈中较晚的时间，因此新的正反馈也会刷新近期度。
 
 ### 晋升 Learnings
 

skill-data/core/references/troubleshooting.md

@@ -372,7 +372,8 @@ makes that rebuild use confirmed counts only; it does not wait for the lock.
 
 Manual `teamai recall feedback --positive <docId>` adds an upvote without adding
 a recall. Confidence caps the upvote-to-recall ratio at 1: more feedback cannot
-exceed that factor's 30% weight or replace recency. This is an activity score,
+exceed that factor's 30% weight. Recency uses the later of the last recall and
+the last upvote, so a fresh upvote also refreshes recency. This is an activity score,
 not proof of knowledge correctness or task success.
 
 ## OpenCode V2 rejects the hooks plugin

src/__tests__/confidence.test.ts

@@ -100,4 +100,32 @@ describe('computeConfidence', () => {
 
     expect(score).toBe(0.7);
   });
+
+  // #1278: a recent upvote with no recall must not be treated as 180 days stale.
+  it('uses lastUpvotedAt for recency when there is no recall (#1278)', () => {
+    const now = new Date().toISOString();
+    const score = computeConfidence({
+      recalledCount: 0,
+      upvotedCount: 1,
+      lastRecalledAt: '',
+      lastUpvotedAt: now,
+    });
+    // base = 0.3, recency = 1.0, ratio = 1.0
+    // confidence = 0.3*0.4 + 1.0*0.3 + 1.0*0.3 = 0.72
+    expect(score).toBe(0.72);
+  });
+
+  it('takes recency from the later of recall and upvote timestamps (#1278)', () => {
+    const oldRecall = new Date(Date.now() - 200 * 24 * 60 * 60 * 1000).toISOString();
+    const recentUpvote = new Date().toISOString();
+    const score = computeConfidence({
+      recalledCount: 1,
+      upvotedCount: 1,
+      lastRecalledAt: oldRecall,
+      lastUpvotedAt: recentUpvote,
+    });
+    // base = 0.4, recency ≈ 1.0 (from upvote), ratio = 1.0
+    // confidence = 0.4*0.4 + 1.0*0.3 + 1.0*0.3 = 0.76
+    expect(score).toBe(0.76);
+  });
 });

src/__tests__/search-index-local-votes.test.ts

@@ -235,4 +235,22 @@ describe('index local votes (#1233)', () => {
     expect((await indexed()).votes).toBe(3.6);
   });
 
+  // #1278: upvoting a never-recalled doc must not apply the cold penalty.
+  it('keeps an upvote-only document hot when last_upvoted_at is recent (#1278)', async () => {
+    await confirmed({
+      version: 2,
+      votes: {
+        [docId]: {
+          recalled_count: 0,
+          upvoted_count: 1,
+          last_recalled_at: '',
+          last_upvoted_at: date,
+        },
+      },
+      deltas: {},
+    });
+    const result = await indexed();
+    expect(result.confidence).toBe(0.72);
+    expect(result.hotness).toBe(1);
+  });
 });

src/maintenance/confidence.ts

@@ -19,21 +19,28 @@ export interface ConfidenceFactors {
  *
  * Formula:
  *   base = min(1.0, recalled * 0.1 + upvoted * 0.3)
- *   recency = max(0, 1.0 - daysSinceLastRecall / 180)
+ *   recency = max(0, 1.0 - daysSinceLastActivity / 180)
+ *     where last activity is the later of lastRecalledAt and lastUpvotedAt (#1278)
  *   ratio = min(1.0, upvoted / max(1, recalled))
  *   confidence = base * 0.4 + recency * 0.3 + ratio * 0.3
  */
 export function computeConfidence(factors: ConfidenceFactors): number {
-  const { recalledCount, upvotedCount, lastRecalledAt } = factors;
+  const { recalledCount, upvotedCount, lastRecalledAt, lastUpvotedAt } = factors;
 
   const base = Math.min(1.0, recalledCount * 0.1 + upvotedCount * 0.3);
 
-  let daysSinceRecall = 180;
-  if (lastRecalledAt) {
-    const elapsed = Date.now() - new Date(lastRecalledAt).getTime();
-    daysSinceRecall = Math.max(0, elapsed / (1000 * 60 * 60 * 24));
+  // A vote with no recall still signals recent interest; use the later timestamp.
+  const lastActivityAt =
+    lastRecalledAt && lastUpvotedAt
+      ? (lastRecalledAt > lastUpvotedAt ? lastRecalledAt : lastUpvotedAt)
+      : (lastRecalledAt || lastUpvotedAt || '');
+
+  let daysSinceActivity = 180;
+  if (lastActivityAt) {
+    const elapsed = Date.now() - new Date(lastActivityAt).getTime();
+    daysSinceActivity = Math.max(0, elapsed / (1000 * 60 * 60 * 24));
   }
-  const recency = Math.max(0, 1.0 - daysSinceRecall / 180);
+  const recency = Math.max(0, 1.0 - daysSinceActivity / 180);
 
   const ratio = Math.min(1.0, upvotedCount / Math.max(1, recalledCount));
 

src/utils/search-index.ts

@@ -350,7 +350,7 @@ interface VoteAggregation {
 
 async function aggregateVotes(votesDir?: string, voteScope?: LocalConfig): Promise<VoteAggregation> {
   const scores = new Map<string, number>();
-  const agg = new Map<string, { recalled: number; upvoted: number; lastRecalled: string }>();
+  const agg = new Map<string, { recalled: number; upvoted: number; lastRecalled: string; lastUpvoted: string }>();
   const contents = voteScope
     ? await (await import('../votes.js')).readIndexVoteFiles(voteScope)
     : await Promise.all((votesDir ? await listFiles(votesDir) : [])
@@ -372,20 +372,23 @@ async function aggregateVotes(votesDir?: string, voteScope?: LocalConfig): Promi
           const upvoted = entry.upvoted_count ?? 0;
           scores.set(docId, (scores.get(docId) ?? 0) + recalled * 0.3 + upvoted * 1.0);
 
-          const existing = agg.get(docId) ?? { recalled: 0, upvoted: 0, lastRecalled: '' };
+          const existing = agg.get(docId) ?? { recalled: 0, upvoted: 0, lastRecalled: '', lastUpvoted: '' };
           existing.recalled += recalled;
           existing.upvoted += upvoted;
           if (entry.last_recalled_at > existing.lastRecalled) {
             existing.lastRecalled = entry.last_recalled_at;
           }
+          if (entry.last_upvoted_at && entry.last_upvoted_at > existing.lastUpvoted) {
+            existing.lastUpvoted = entry.last_upvoted_at;
+          }
           agg.set(docId, existing);
         }
       } else {
         const votes = (parsed as unknown as UserVotes).votes;
         for (const [docId, entry] of Object.entries(votes)) {
           scores.set(docId, (scores.get(docId) ?? 0) + 1);
 
-          const existing = agg.get(docId) ?? { recalled: 0, upvoted: 0, lastRecalled: '' };
+          const existing = agg.get(docId) ?? { recalled: 0, upvoted: 0, lastRecalled: '', lastUpvoted: '' };
           existing.recalled += 1;
           if (entry.at > existing.lastRecalled) existing.lastRecalled = entry.at;
           agg.set(docId, existing);
@@ -403,6 +406,7 @@ async function aggregateVotes(votesDir?: string, voteScope?: LocalConfig): Promi
       recalledCount: data.recalled,
       upvotedCount: data.upvoted,
       lastRecalledAt: data.lastRecalled,
+      lastUpvotedAt: data.lastUpvoted || undefined,
     }));
   }