Journal Review

/journal-review Workflow

Inputs

User provides:

• Review period: "this week", "last week", "last N days", "this sprint", a date range (YYYY-MM-DD to YYYY-MM-DD), or omitted (defaults to "this week")
• Optional: category filter (decisions, learnings, actions, themes, or all)

Scope parameters:

• JOURNAL_BASE: ~/journal/ (hardcoded, matches /journal and /journal-recall skills)
• REVIEW_CATEGORIES: decisions, learnings, actions, themes
• DECISION_SIGNALS: "decided", "chose", "went with", "opted for", "tradeoff", "picked", "selected", "decision:"
• LEARNING_SIGNALS: "learned", "discovered", "figured out", "TIL", "gotcha", "insight", "realization", "aha"
• ACTION_SIGNALS: "- [ ]", "TODO", "follow up", "need to", "action item", "next step"
• Default review period: "this week" (Monday of current week through today)

Step 0 — Configure Review Period

Action: Parse user input to determine the date range for the review.

Date resolution rules:

1. "this week" (or omitted): Monday of current week through today (inclusive)
2. "last week": Monday through Sunday of previous week
3. "last N days": Today minus N through today (inclusive)
4. "this sprint": Last 14 days (2-week sprint default)
5. Date range (YYYY-MM-DD to YYYY-MM-DD): Exact range specified
6. Single date: That date only

Validation:

• Start date must not be in the future
• End date must be >= start date
• Range must not exceed 90 days (safety limit)
• If validation fails, report error and FAIL

Category filter:

• If user specifies a category, only scan for that category
• Default: all categories (decisions, learnings, actions, themes)

Tool declarations: Bash (date calculations)

Checkpoint: Review period resolved to concrete start/end dates, categories determined

Step 1 — Scan Daily and Meeting Entries

Action: Read all daily and meeting entries within the review period.

File discovery:

1. Use Glob to find daily entries: $JOURNAL_BASE/daily/*.md
2. Filter by date range: parse YYYY-MM-DD from filename, include if within [start, end]
3. Use Glob to find meeting entries: $JOURNAL_BASE/meetings/*.md
4. Filter meetings by date: parse YYYY-MM-DD prefix from filename
5. Read all matching files

If no entries found:

• Report: "No daily or meeting entries found for {date range}. Nothing to review."
• Verdict: PASS: no entries found for review period (searched daily/ and meetings/)
• STOP (do not proceed to Step 2)

Content extraction per file:

• Store full content indexed by file path and date
• Extract section content for targeted scanning in Step 2

Tool declarations: Glob (find files), Read (file content), Bash (date filtering)

Checkpoint: All entries for review period loaded into working memory

Step 2 — Extract Candidates

Action: Scan loaded entries for each active category using signal-word matching and contextual analysis.

Resilience note: Scan the full file content for signal words using grep-style matching across the entire entry text, not only named sections. Section-scoped matches (e.g., content found under ## Decisions Made) are treated as higher-confidence candidates, but signal matches anywhere in the file are included. If an entry is missing expected sections (e.g., no ## Learnings heading), log a warning but still scan the full content.

2a — Unlogged Decisions

Scan strategy:

1. Search the full entry content for decision-signal language: "decided", "chose", "went with", "opted for", "tradeoff", "picked", "selected", and variations (case-insensitive)
2. Also scan ## Decisions Made sections in daily entries for inline decisions not linked to decisions/ files (matches here are higher-confidence)
3. For each match, extract:
   • Source file and date
   • Decision text: the sentence or bullet containing the signal word, plus 1-2 lines of surrounding context
   • Inferred topic: a short descriptive name for the decision (e.g., "Use contrib/ directory for personal skills")
4. Exclude matches that are:
   • Inside wikilinks to existing decision files (e.g., [[decisions/2026-02-23-worktree-isolation]])
   • Clearly referencing past decisions already recorded (e.g., "as we decided in the ADR...")

2b — Unlogged Learnings

Scan strategy:

1. Search entry content for learning-signal language: "learned", "discovered", "figured out", "TIL", "gotcha", "insight", "realization", and variations
2. Also scan ## Learnings sections and **Learning:** fields in work session blocks
3. For each match, extract:
   • Source file and date
   • Learning text: the sentence or bullet containing the signal word, plus context
   • Inferred topic: a short descriptive name (e.g., "Git worktrees are lightweight")
4. Exclude matches that:
   • Link to existing learning files (e.g., [[learnings/project-recovery-strategy]])
   • Are trivial observations (single words, vague statements)

2c — Untracked Action Items

Scan strategy:

1. Search for unchecked checkboxes: - [ ] (not - [x])
2. Search for TODO markers: "TODO", "FIXME", "HACK" (case-insensitive)
3. Search for follow-up language: "follow up", "need to", "action item", "next step"
4. Also scan ## Tomorrow's Priorities, ## Action Items, ## Follow-up, ## Next Steps sections
5. For each match, extract:
   • Source file and date
   • Action text: the specific action item or TODO
   • Assignee: if present (e.g., @person in meeting notes)
   • Due date: if mentioned
6. Cross-reference: check if the same action item text appears as - [x] (completed) in a later daily entry within the vault. If so, mark as "completed" and exclude from candidates.

2d — Recurring Themes

Scan strategy:

1. Analyze all loaded entries for recurring topics:
   • Project names: Extract from YAML frontmatter projects: field and **Project:** lines
   • Technologies/tools: Mentioned multiple times across entries
   • Problem patterns: Similar blockers, challenges, or concerns appearing in multiple entries
   • People/teams: Recurring collaborators or stakeholders
2. A theme is "recurring" if it appears in 2+ entries within the review period
3. For each theme, extract:
   • Theme name: descriptive label
   • Frequency: number of entries mentioning it
   • Dates: which entries
   • Context snippets: representative excerpts from each mention

Tool declarations: Grep (signal-word search), Read (section extraction — files already loaded from Step 1)

Checkpoint: All candidates extracted and categorized

Step 3 — Cross-Reference Existing Entries

Action: For decision and learning candidates, check whether a formal entry already exists that covers the same topic.

Decisions cross-reference:

1. Use Glob to list all files in $JOURNAL_BASE/decisions/
2. Read the title (from # ADR: heading or YAML title: field) of each existing decision file
3. For each decision candidate from Step 2a, compare the candidate's inferred topic against existing decision titles and content summaries
4. Semantic matching: The candidate topic and existing entry title/context describe the same decision, even if worded differently. For example, candidate "chose contrib/ over skills/ for journal" matches existing ADR titled "Journal Distribution Model" if the content discusses the same choice.
5. If a confident semantic match is found, move the candidate to the Filtered candidates list (not silently dropped — reported in Step 4). Record the matched existing entry and the reason for filtering.
6. If uncertain whether a candidate matches an existing entry, keep the candidate but annotate it: "Possible duplicate of: {existing entry title}."
7. If no match, keep the candidate

Learnings cross-reference:

1. Use Glob to list all files in $JOURNAL_BASE/learnings/
2. Read the title (from # Learning: heading or YAML title: field) of each existing learning file
3. For each learning candidate from Step 2b, compare against existing learning titles and content summaries
4. Apply the same semantic matching as for decisions
5. If a confident semantic match is found, move to Filtered candidates list with matched entry and reason
6. If uncertain, keep the candidate with a "Possible duplicate of:" annotation
7. If no match, keep the candidate

Confidence and audit:

• Every filtered candidate is preserved in a Filtered candidates list with: the candidate text, the matched existing entry, and a one-line reason explaining why it was considered a match.
• This list is presented to the user in Step 4 so they can audit cross-reference decisions and override any incorrect matches.

Tool declarations: Glob (list existing entries), Read (entry titles/content)

Checkpoint: Candidates filtered — only genuinely unlogged items remain; filtered candidates preserved for user audit

Step 4 — Present Candidates and Get Approval

Action: Present remaining candidates to the user, grouped by category, and collect approval/dismissal decisions.

Pagination: If any category contains more than 10 candidates, present the top 10 (ranked by signal confidence: section-scoped matches first, then recency) and note: "{N} additional candidates found. Say 'show more {category}' to see them."

Presentation format:

For each active category that has candidates, present a summary block:

## Unlogged Decisions (N candidates)

### 1. {Inferred Topic}
**Source:** daily/{date}.md, line ~{N}
**Signal:** "{signal phrase in context}"
**Context:** {1-3 sentences of surrounding context}
**Recommendation:** Create ADR? [approve / dismiss]

### 2. {Inferred Topic}
...

## Unlogged Learnings (N candidates)

### 1. {Inferred Topic}
**Source:** daily/{date}.md
**Signal:** "{signal phrase in context}"
**Context:** {1-3 sentences of surrounding context}
**Recommendation:** Create learning entry? [approve / dismiss]

...

## Untracked Action Items (N candidates)

### 1. {Action Text}
**Source:** daily/{date}.md
**Status:** Open (not found as completed in later entries)
**Age:** {N days since entry date}

...

## Recurring Themes (N themes)

### 1. {Theme Name}
**Frequency:** Mentioned in {N} entries
**Dates:** {date1}, {date2}, ...
**Snippets:** {representative excerpts}
**Note:** This is informational — no entry created for themes.

...

## Filtered by Cross-Reference (N items)

The following candidates were excluded because they appear to match existing entries.
If any were filtered incorrectly, say "restore {category} {number}" to promote them.

### 1. {Candidate Topic}
**Source:** daily/{date}.md
**Signal:** "{signal phrase in context}"
**Matched to:** {existing entry filename and title}
**Reason:** {one-line explanation of why it was considered a match}

...

If no candidates in any category:

• Report: "No unlogged items found for {date range}. Your journal entries are well-formalized!"
• Verdict: PASS: no candidates found (reviewed N entries across N days)
• STOP (do not proceed to Step 5)

Interaction:

1. Present candidates grouped by category (top 10 per category if more than 10 exist)
2. Present the Filtered by Cross-Reference section so the user can audit what was excluded
3. Use AskUserQuestion to ask: "Which items would you like to promote to formal entries? You can specify by number (e.g., 'Decisions: 1, 3; Learnings: 2') or say 'all', 'none', 'all decisions' / 'all learnings', 'show more {category}', or 'restore {category} {number}' to recover a filtered item."
4. Parse user response to determine which candidates are approved
5. If user says "show more {category}", present the next batch of candidates for that category
6. If user says "restore {category} {number}", move the filtered candidate back to the active list for approval
7. Recurring themes are informational only — no entries are created for them

Tool declarations: AskUserQuestion (user approval)

Checkpoint: Approval list finalized

Step 5 — Create Approved Entries

Action: For each approved candidate, create a formal journal entry using the same templates and conventions as the /journal skill.

For approved decisions:

1. Filename: $JOURNAL_BASE/decisions/YYYY-MM-DD-{sanitized-topic}.md
   • YYYY-MM-DD = date of the source daily entry where the decision was found
   • sanitized-topic: strip path separators, remove .., remove chars outside [a-zA-Z0-9_-], lowercase, limit 100 chars
2. Template: Use embedded decision template (see Embedded Templates below)
3. Fill template:
   • {Decision Name} = inferred topic from Step 2a
   • date = source entry date
   • ## Context = extracted context from the daily entry
   • ## Decision = the decision text from the signal match
   • ## Rationale = any surrounding reasoning from the daily entry, or <!-- Fill in rationale -->
   • **Project:** = project from source entry's YAML frontmatter or session block
   • Cross-link to source daily entry: [[daily/YYYY-MM-DD]]
4. Verify path starts with $JOURNAL_BASE/ (traversal protection)
5. Check for existing file at target path — if exists, warn user and skip (do not overwrite)
6. Write file

For approved learnings:

1. Filename: $JOURNAL_BASE/learnings/{sanitized-topic}.md
   • sanitized-topic: same sanitization as decisions
2. Template: Use embedded learning template (see Embedded Templates below)
3. Fill template:
   • {Topic Name} = inferred topic from Step 2b
   • date = source entry date
   • ## Context / **Why I learned this:** = extracted context
   • ### What I Discovered = the learning text
   • **Project:** = project from source entry
   • Cross-link to source daily entry: [[daily/YYYY-MM-DD]]
4. Verify path, check existing, write file

For approved action items:

Action items are NOT created as new journal entries. Instead, they are reported as a summary list for the user to track manually. The skill does not create a tracking system.

Output for action items:

## Open Action Items Summary

| # | Action | Source | Date | Age |
|---|--------|--------|------|-----|
| 1 | {action text} | daily/{date}.md | {date} | {N} days |
| 2 | ... | ... | ... | ... |

These items were found as open (unchecked) in your daily entries.
Consider adding them to your current daily entry's Tomorrow's Priorities
or closing them with `- [x]` in the source file.

Post-creation:

1. Report all created files with absolute paths
2. Report dismissed candidates (for reference)
3. Report action items summary (if any)
4. Report recurring themes (informational)

Verdict:

• If entries were created: PASS: created N entries (M decisions, K learnings) from review of {date range}
• If user dismissed all: PASS: all candidates dismissed, no entries created (reviewed N daily entries)
• If error writing any file: FAIL: {reason} (N of M entries written successfully)

Tool declarations: Write (new files), Bash (date operations, path sanitization), Glob (check existing files)

Checkpoint: All approved entries created, results reported

Embedded Templates

The following templates are used for entries created by this skill. They are identical to the /journal skill's embedded templates to ensure consistency across the journal vault. On-disk templates at ~/journal/templates/{type}.md override these if present.

IMPORTANT — template duplication policy: At implementation time, templates were copied character-for-character from /journal SKILL.md v1.0.0 (the authoritative source). Each embedded template includes a version tracking comment. If /journal templates change, re-sync these templates.

decision.md

---
title: Decision Name
date: YYYY-MM-DD
status: accepted | rejected | superseded | deprecated
tags: [decision, architecture]
projects: []
---

# ADR: {Decision Name}

## Status
**Status:** Accepted
**Date:** YYYY-MM-DD
**Deciders:** <your-name>
**Project:** [[project-name]]

## Context
<!-- What is the issue that we're seeing that is motivating this decision? -->

## Decision
<!-- What is the change that we're proposing? -->

## Rationale
<!-- Why are we making this decision? -->

### Options Considered
1. **Option A:**
   - Pros:
   - Cons:

### Why We Chose This


## Consequences
### Positive
-

### Negative
-

### Neutral
-

## Implementation
**Implemented in:** [[project-name]]
**Date implemented:** YYYY-MM-DD
**Commits:**

## Related Decisions
- [[decisions/other-decision]]

## References
-

learning.md

---
title: Topic Name
date: YYYY-MM-DD
tags: [learning]
category: technical | pattern | tool
confidence: beginner | intermediate | advanced
---

# Learning: {Topic Name}

## Context
**When:** [[daily/YYYY-MM-DD]]
**Project:** [[project-name]]
**Why I learned this:**

## The Learning

### What I Discovered


### How It Works


### Why It Matters


## Code Example
```python
# Example code

Gotchas / Pitfalls

Related Concepts

• [[other-learning]]

References

Application

Used in: [[project-name]] Date applied: YYYY-MM-DD Outcome:

## Timestamped Artifacts

**Not applicable:** Journal review creates permanent journal entries, not workflow artifacts. The review results are communicated directly to the user during the session.

## Bounded Iterations

**Not applicable:** The approval loop is bounded by the number of candidates (finite, extracted from a finite set of entries). There is no revision loop — the user approves or dismisses each candidate once.

## Archive on Success

**Not applicable:** Journal entries are the final output, not intermediate artifacts requiring archival.