Year

Yearly Review

Generates a comprehensive yearly review without asking questions. Chains data upward from quarterly and monthly reviews, recomputes where those don't exist, and writes a [!yearly-review]- block into the yearly note, then appends a minimal space for the user's own reflections.

Language Detection

Before generating any content, detect the user's writing language. Read the 5 most recent daily notes (periodic/daily/YYYY-MM-DD.md). In non-frontmatter, non-wikilink, non-tag text, count Cyrillic vs Latin characters. If Cyrillic > 30% → write the entire review in Russian. Otherwise → English.

Apply to ALL section headers, metric labels, table column names, inference lines (→), characterization labels, and participation prompts. Callout types and wikilinks remain unchanged regardless of detected language.

Yearly Note Format

Path: periodic/yearly/YYYY.md

Frontmatter (exact from template):

---
tags:
  - periodic/year
reviewed: false
cssclasses:
  - hide-backlinks
created: YYYY-MM-DDTHH:mm:ssZ
updated: YYYY-MM-DDTHH:mm:ssZ
---

Note: yearly notes have no up: field — they are the top of the hierarchy.

If the yearly note exists — find [!yearly-review]- and replace it. Otherwise create with template, then append after [!success]-.

Execution Flow

User: "yearly review" / "итоги года" / "годовой обзор"
    |
1. Determine current year (YYYY)
    |
2. Find or create periodic/yearly/YYYY.md
    |
3. Detect language from last 5 daily notes
    |
4. Gather IN PARALLEL:
   a. Year in numbers — velocity across all 12 months
   b. Intellectual diet — source breakdown by type and category
   c. Theme trajectory — Q1 vs Q4 themes, emergent/abandoned/core;
      also read user-written sections below [!quarterly-review]- in each quarterly note
   d. Project portfolio — all year outcomes + multi-year drag
   e. Synthesis ratio — per quarter trend
   f. Previous yearly note — for year-over-year comparison
    |
5. For each section: collect data → derive one "→" inference from the specific pattern
    |
6. Generate review: numbers → diet → trajectory → projects →
   synthesis → year sentence → next year priority
    |
7. Write [!yearly-review]- callout into yearly note
    |
8. Append user participation section below the callout (outside it)
    |
9. Minimal chat confirmation

Year in Numbers

Compute velocity for each of the 12 months, then aggregate.

Per-month computation (all 12 months in parallel):

# Notes created (run for each MM from 01 to 12):
obsidian search query="[created: YYYY-MM]" path=base/notes total
obsidian search query="[created: YYYY-MM]" path=base/additions total

# Tasks closed (run for each MM):
obsidian search query="✅ YYYY-MM" total

# Sources processed (run for each MM):
obsidian search query="[status: 🟩] [end: YYYY-MM]" path=sources total

Aggregate:

• Total for year
• Peak month: month with highest combined activity
• Dead months: months where notes=0 AND tasks=0 AND sources=0
• Consistency score: (12 - dead months) / 12 × 100% Consistency = share of months with any activity. 100% = active every month. Lower = feast-or-famine pattern.

Year-over-year: If periodic/yearly/YYYY-1.md exists and has a [!yearly-review]- block, extract its totals for comparison. Show delta with ↑/↓.

> **Year in numbers:**
> - Notes: 187 (↑ from 134 last year)
> - Tasks closed: 412 (↓ from 489)
> - Sources processed: 43 (↑ from 31)
> - Peak month: October (notes: 28, tasks: 67, sources: 9)
> - Dead months: 2 (February, July)
> - Consistency: 83% (10 of 12 months active)

→ Inference: After showing numbers, derive one data-specific observation. Look for:

• All metrics ↑ vs last year → growth year; what structural change made this possible?
• One metric ↓ while others ↑ → something shifted (notes ↑ but tasks ↓ = more thinking, less doing)
• Dead months > 3 → sporadic pattern; the habit is fragile — what collapsed in those months?
• Consistency < 60% → the work is concentrated in bursts; useful to understand what sustains the active periods

Write the inference in detected language. Skip if no clear pattern.

Intellectual Diet

Breakdown of all sources completed (end: YYYY- + status: 🟩) by type and category.

Source types

All valid source tags in this vault:

source/article/paper
source/article/resource
source/book
source/course
source/cinematic/movie
source/cinematic/series
source/cinematic/anime
source/podcast
source/video/recording
source/video/playlist
source/music/album
source/music/tracklist
source/game

# Get all sources completed this year, then count by tag:
obsidian search query="[status: 🟩] [end: YYYY]" path=sources
# From those files, count occurrences of each tag above.
# Or look up each type directly:
obsidian tag name="source/book" verbose
obsidian tag name="source/article/paper" verbose
obsidian tag name="source/article/resource" verbose
obsidian tag name="source/course" verbose
obsidian tag name="source/cinematic/movie" verbose
obsidian tag name="source/cinematic/series" verbose
obsidian tag name="source/cinematic/anime" verbose
obsidian tag name="source/podcast" verbose
obsidian tag name="source/video/recording" verbose
obsidian tag name="source/video/playlist" verbose
obsidian tag name="source/music/album" verbose
obsidian tag name="source/music/tracklist" verbose
obsidian tag name="source/game" verbose
# Cross-reference each result with the completed set for YYYY.

Source categories

# Read completed sources from: obsidian search query="[status: 🟩] [end: YYYY]" path=sources
# Extract category: frontmatter field from each file → count by category, show top 5

> **Intellectual diet:**
> - By type: 📚 books: 12 | 📄 articles/resources: 11 | 📑 papers: 7 | 🎬 video/recordings: 5 | 📺 video/playlists: 3 | 🎓 courses: 2 | 🎬 movies: 2 | 📡 podcasts: 1
> - Top categories: [[knowledge management]] (11), [[artificial intelligence]] (9), [[productivity]] (7), [[writing]] (5), [[health]] (3)
> - Dominant type: books (29% of total)

If one type > 60% of total — flag it: ⚠️ Heavy bias toward [type] — consider diversifying sources.

→ Inference: After showing diet, derive one data-specific observation. Look for:

• Diet dominated by passive formats (articles, videos) vs active (books, courses, papers) → breadth vs depth signal
• Top categories in diet diverge from core themes in knowledge base → are you studying what you're actually thinking about?
• Very narrow category coverage (2–3 categories dominate) → potential echo chamber; what's being ignored?
• Diet is varied and matches theme trajectory → strong alignment between learning and thinking

Write the inference in detected language. Skip if no clear pattern.

Multi-Quarter Theme Trajectory

Reveals what emerged, what faded, and what held throughout the year. Also surfaces what the user themselves identified as important through their quarterly focus statements.

Data source (priority order)

1. Quarterly reviews — if periodic/quarterly/YYYY-Q1.md through YYYY-Q4.md exist and have [!quarterly-review]- blocks, extract their "Theme Drift" sections
2. User-written quarterly sections — read text BELOW the [!quarterly-review]- callout in each quarterly note (user's "Focus for next quarter" and "My conclusions"). Surface any stated intentions that connect to theme patterns.
3. Fallback — grep wikilinks in daily notes for Q1 (YYYY-01 to YYYY-03) and Q4 (YYYY-10 to YYYY-12), count frequency per meta-note

Classification

• Emergent: appeared in Q3 or Q4, absent in Q1 and Q2 (new focus area this year)
• Abandoned: prominent in Q1/Q2, absent in Q3/Q4 (lost momentum)
• Core: present in all 4 quarters (sustained intellectual interest)
• Seasonal: appears in exactly one quarter

> **Theme trajectory:**
> - Emergent: [[machine learning]] (appeared Q3, dominant Q4), [[writing systems]] (Q4 only)
> - Abandoned: [[linux administration]] (Q1 top, gone by Q3), [[economics]] (Q1–Q2 only)
> - Core (all year): [[knowledge management]], [[learning]], [[productivity]]
> - Seasonal: [[health]] (Q1 only)

→ Inference: After showing trajectory, derive one data-specific observation. Look for:

• Many abandoned vs few core → intellectually nomadic year; broad exploration without depth
• Strong emergent theme in Q4 → discovered something important late; worth making it explicit next year
• Core theme with no completed projects → consistent interest but no shipping; what's the gap?
• User's quarterly focus statements align with actual theme data → intentional direction held all year

Write the inference in detected language. Skip if no clear pattern.

Project Portfolio

Full year view of project activity and execution rate.

Completed this year

obsidian search query="tag:#project [status: 🟩]"
obsidian search query="tag:#project [status: 📢]"
# Filter: keep only files where updated: frontmatter falls within YYYY

Frozen this year

obsidian search query="tag:#project [status: ❄]"
# Filter: keep only files where updated: frontmatter falls within YYYY

Started this year

obsidian search query="tag:#project [status: 🟦]"   # in progress
obsidian search query="tag:#project [status: 🟥]"   # todo
# Filter: keep only files where created: frontmatter falls within YYYY

Multi-year drag

obsidian search query="tag:#project [status: 🟦]"   # in progress
obsidian search query="tag:#project [status: 🟥]"   # todo
# Filter: keep only files where created: predates YYYY (from previous years)

Completion rate = completed / (completed + frozen + multi-year drag) × 100% Of all projects that reached any resolution this year (completed or frozen) plus those carried from before, what share actually finished?

> **Project portfolio:**
> - Completed (5): [[Blog Series Part 1]] 📢, [[Home Lab Setup]] 🟩, [[Reading Tracker v2]] 🟩, [[Podcast Outline]] 📢, [[Note Sync Script]] 🟩
> - Frozen (3): [[Course Notes App]] ❄️, [[Spanish Learning Plan]] ❄️, [[Video Essay Draft]] ❄️
> - Started (8): ...
> - Multi-year drag (2): [[Archive Reorganization]] 🟦 (from 2024), [[API Integration]] 🟥 (from 2023)
> - Completion rate: 42% (5 completed / 12 resolvable)

If completion rate < 30%: ⚠️ Low completion rate — starting is easy, finishing is the bottleneck. If multi-year drag > 2 projects: ⚠️ N projects carried from previous years — consider archiving or resetting.

→ Inference: After listing portfolio, derive one data-specific observation. Look for:

• High frozen count → projects are being started optimistically but scope or motivation doesn't hold
• Multi-year drag accumulating year over year → the system isn't clearing historical commitments
• Started count >> Completed count → are projects being designed too large? Or is scope expanding after start?
• Completion rate > 60% → strong execution year; what specifically worked that could be repeated?

Write the inference in detected language.

Synthesis Ratio Trend

Shows whether synthesis efficiency improved or declined across the year.

Compute ratio (notes created / sources processed) for each quarter:

> **Synthesis ratio:**
>
> | Q1  | Q2  | Q3  | Q4  | Year |
> |-----|-----|-----|-----|------|
> | 1.4 | 2.1 | 3.2 | 1.8 | 2.1  |
>
> *Scale: >2.0 = strong synthesis, 1.0–2.0 = balanced, 0.5–1.0 = consuming > creating, <0.5 = synthesis gap*
> Peak: Q3. Trend: ↑ Q1→Q3, ↓ Q3→Q4.
> Year average: 2.1 (balanced).

→ Inference: After showing trend, derive one data-specific observation. Look for:

• Synthesis dropping consistently Q1→Q4 → reading appetite grew faster than processing capacity
• Synthesis high in low-activity months → when less is happening, more gets processed
• Consistently low (<1.0) all year → systematic habit gap; each new source needs a note before the next one opens
• Peak synthesis quarter matches high project completion quarter → synthesis and shipping are connected

Write the inference in detected language.

The Year in One Sentence

A single factual characterization derived from the dominant pattern — not inspirational, not motivational. Just accurate.

Derive from the data:

> **Year in one sentence:**
> Год одной темой: knowledge management занял 38% всех упоминаний — это либо глубина, либо туннельное зрение.

Write the label and characterization in detected language. One sentence. Name the exact metric or number that triggered the characterization. Do not soften or inflate — be accurate.

Priority for Next Year

One concrete direction derived from the year's weakest or most significant signal. Not a wish — a logical next step from the data. Also check user-written quarterly sections for any stated intentions about next year.

Priority logic (pick the highest-priority applicable rule):

1. Completion rate < 30% → "Не начинать новые проекты пока не закроешь [N stuck projects]"
2. Multi-year drag > 2 → "Первым делом: решить судьбу [oldest stuck project]"
3. Synthesis ratio < 1 for 3+ quarters → "Добавить шаг синтеза между чтением и следующим источником"
4. Dead months > 3 → "Снизить объём в пиковые месяцы, чтобы не выгорать в мёртвые"
5. Intellectual diet heavily biased (>60% one type) → "Расширить диету: добавить [underrepresented source type]"
6. Theme abandoned mid-year with no notes → "[[Abandoned theme]] требует либо закрытия, либо осознанного возврата"
7. Emergent theme dominant in Q4 → "[[Emergent theme]] оказался неожиданно важным — стоит сделать его явным приоритетом"

> **Priority for next year:**
> Коэффициент синтеза падал 3 квартала подряд — добавить промежуточный шаг между обработкой источника и следующим чтением. Например: заметка до открытия нового источника.

One actionable sentence in detected language, with the specific number or fact that justifies it.

Output Format

> [!yearly-review]- Yearly review — YYYY
> **Year in numbers:**
> - Notes: N (↑/↓ from last year)
> - Tasks closed: N
> - Sources processed: N
> - Peak month: Month (notes: N, tasks: N, sources: N)
> - Dead months: N (Month, Month)
> - Consistency: N% (N of 12 months active)
> → [inference about year pattern — only if clear]
>
> **Intellectual diet:**
> - By type: 📚 books: N | 📄 articles: N | 🎬 video: N | ...
> - Top categories: [[cat]] (N), [[cat]] (N)
> → [inference about diet composition — only if clear]
>
> **Theme trajectory:**
> - Emergent: [[theme]] (appeared QN)
> - Abandoned: [[theme]] (gone by QN)
> - Core: [[theme]], [[theme]]
> → [inference about intellectual arc of the year — only if clear]
>
> **Project portfolio:**
> - Completed (N): [[Project]] 📢, [[Project]] 🟩
> - Frozen (N): [[Project]] ❄️
> - Started (N): N projects
> - Multi-year drag (N): [[Project]] (from YYYY)
> - Completion rate: N%
> → [inference about execution capacity — only if clear]
>
> **Synthesis ratio:**
>
> | Q1 | Q2 | Q3 | Q4 | Year |
> |----|----|----|----|----|
> | N  | N  | N  | N  | N  |
>
> *Scale: >2.0 = strong, 1.0–2.0 = balanced, 0.5–1.0 = consuming, <0.5 = gap*
> → [inference about synthesis trend — only if clear]
>
> **Year in one sentence:**
> [Characterization label]: [one sentence in detected language]
>
> **Priority for next year:**
> [One actionable sentence]

Rules:

• Write into note — never just output to chat
• Collapsed by default (- suffix)
• Callout title includes year: [!yearly-review]- Yearly review — 2026
• All labels translated to detected language
• Skip sections with no content
• Skip "→" inference lines where no clear pattern exists — never write generic lines
• Every reference = [[wikilink]]
• Flags (⚠️) only for patterns that cross clear thresholds — don't flag minor deviations

User Participation Sections

After the [!yearly-review]- callout, appended outside it (in the note body), with a horizontal rule separator.

The yearly note is the top of the hierarchy — there is no higher-level review to feed. This section is for the user's personal synthesis: what the year actually meant, what they want to carry forward.

Default form (always):

---
**Мои выводы за год / My reflections on the year:**

**Намерение на следующий год / My intention for [YYYY+1]:**

Extended form (when review data shows a specific strong signal):

---
*[One direct question from the review's most significant finding — e.g., "[[X theme]] оказался заброшен к Q3 без единой заметки — это завершено или просто забыто?" / "[[X theme]] was abandoned by Q3 without a single note — resolved or forgotten?"]*

**Мои выводы за год / My reflections on the year:**

**Намерение на следующий год / My intention for [YYYY+1]:**

Write the italic question in detected language. Use extended form only when the signal is unambiguous.

Unlike lower-level review notes, this is not read by a higher-level review. This section exists purely for the user — a space for personal synthesis at the highest level of the review system.

Chat Output

Review written → periodic/yearly/2026.md

Notes: 187 (↑ from 134). Tasks: 412. Sources: 43.
Diet: articles dominant (42%). Top: knowledge management, AI.
Themes: knowledge management core all year; linux abandoned Q3.
Projects: 5/12 completed (42%). 2 multi-year drag.
Synthesis: avg 2.1, peak Q3.
Year: [characterization in 1 line]. Priority: [priority in 1 line].

If note was created — first line: Created periodic/yearly/2026.md + review. Adapt language of confirmation to match detected language.