Parse plain-language time reports into structured Notion logs
Time Ledger parses plain-language time reports into your own Notion database, asking instead of guessing when unsure.
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Why it matters
Track time spent on activities by speaking naturally-report "read papers 2h, gym 1h" and the skill parses it into structured Notion database rows (activity, minutes, date, compounding tag), asking for confirmation on anything uncertain rather than guessing.
Outcomes
What it gets done
Parse natural language time reports into activity categories, durations, and dates
Write structured time entries to your Notion database via the official connector
Flag uncertain entries as To-confirm and batch all clarifying questions into one message
Reconcile incomplete ledger rows by querying To-confirm entries and updating them after user answers
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-time-ledger | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
Time Ledger
Time Ledger parses plain-language time reports into structured rows in the user's own Notion database via the official Notion connector, marking anything uncertain as To-confirm and batching those questions rather than fabricating a duration, date, or category. Use it whenever the user reports time spent in natural language, or asks to tidy up or review their time ledger - requires a duplicated copy of the companion Notion template and connector access.
What it does
Time Ledger is conversational time tracking: the user reports time spent in plain language, such as "read papers 2h, gym 1h, did a leetcode," and the skill parses it into structured rows - activity, minutes, date, and an optional compounding tag - written to the user's own Notion database through the official Notion connector. Its core design is what it calls an honesty contract: anything uncertain becomes a To-confirm row and is batch-asked about, never fabricated, because "a log that quietly invents durations is worse than no log." On the first write of a session it uses Notion search to find the database, filtering for type database rather than a page, whose title contains "time-ledger," reading its data_source_id as the parent for all subsequent create-pages/query calls that session - nothing is pasted or manually configured, and it asks the user to disambiguate if more than one match is found. The companion Notion template defines a fixed field schema with controlled select enums that must be copied exactly: Entry (title), Activity (Reading/Coding/Practice/Fitness/Investing/Meeting/Writing/Life/Other), Minutes (number), Date, which must be written as the expanded "date:Date:start": "YYYY-MM-DD" form since a bare Date value fails with HTTP 400, Status (To-sort/To-confirm/Done), Compounding (Compounding/Consuming/Neutral), and Notes (text). Direct-report parsing rules are concrete: reading material maps to Reading, coding to Coding, leetcode to Practice, gym or running to Fitness, markets or research to Investing, meetings to Meeting, docs to Writing, meals/commute/chores to Life; duration cues map "two hours" to 120, "an hour" to 60, "half an hour" to 30, "a while" to about 30, marked To-confirm as an estimate, and "all morning" to about 180; "today"/"yesterday" resolve to the user's local date, defaulting to today when unspecified; multiple activities in one report split into separate rows, defaulting to additive totals plus one To-confirm row to check that assumption; and the Compounding tag is only applied when obvious, Compounding for a reusable asset like learning or building, Consuming only if the user volunteers it, otherwise left blank rather than guessed.
When to use - and when NOT to
Use it when the user reports time spent in natural language, says "log it," "log my time," "time ledger," or "tidy up my time ledger," or asks where their time went. In batch-reconcile mode, triggered by "tidy up my time ledger," it queries every row with Status in To-sort, To-confirm, or empty, updates the certain ones to Done, and bundles every remaining question into a single message rather than interrogating item by item. It explicitly does not judge the user's Consuming hours - the ledger is described as "a mirror, not a critic" - and by design it is self-report only, deliberately not auto-tracking apps or screens, since an auto-tracker "knows what was open, not why the time was spent." It requires the user's own Notion workspace, a duplicated copy of the companion template database, and the official Notion connector granted access to that specific database - connector and skill setups currently live on paid Claude tiers.
Inputs and outputs
Input is a plain-language time report or the "tidy up" command; output is one Notion page (row) per activity block, written via create-pages with the exact field schema above, or updated via update-page during reconciliation. A worked direct-report example from the source: "log it: read ML system design 2h, gym 1h, did a leetcode" produces three logged entries, with the LeetCode one marked To-confirm because no duration was stated and a 20-minute estimate was guessed and flagged for confirmation. Four documented pitfalls and fixes: a bare Date property returns HTTP 400, fixed with the date:Date:start expansion; a known Notion MCP bug (notion-mcp-server#121) can silently drop the expanded date field even on a successful create-pages call, so the row should be read back after the session's first create and backfilled with update-page if Date came back empty; a search for "time-ledger" can return example-row pages instead of the database itself, fixed by filtering for type database; and a model-clock-vs-user-timezone mismatch around midnight should default "today" to the user's local date and ask when it's genuinely ambiguous.
Integrations
Writes and updates rows only inside the single user-granted Notion database via the official Notion connector (MCP) - no shell commands, no network fetches, and no credentials handled directly by the skill. On claude.ai, Notion's write tools default to requiring approval, so the first write in a session popping an approval prompt is expected behavior, not a hang. It names one related, separate skill, @trading-ledger, applying the same parse-plain-language-into-your-own-Notion-database-and-ask-instead-of-guessing pattern to trading journals covering entry thesis, plan, and emotion.
Who it's for
Anyone who wants to log time spent in their own words rather than filling out a structured form, with the guarantee that anything the parser is unsure about gets asked about in one batched message rather than silently invented - useful for a running personal time ledger that stays honest about its own uncertainty.
Source README
time-ledger
English | 简体中文
Track your time in one sentence. You say what you did in plain language - "read ML papers for two hours, hit the gym for one, did a LeetCode problem" - and an AI parses it into structured activity / minutes / date and writes it to your own Notion database. When it isn't sure, it asks you back instead of guessing.
Not a timer. Not a form. A mirror for whether your hours are actually compounding.
You: read ML system design for two hours, gym for one, did a leetcode
AI: Logged 3 entries ✅
· Reading · ML system design · 120min · compounding
· Fitness · gym · 60min
· LeetCode · ~20min ❓ to-confirm: you didn't say how long — I guessed 20min, right?
Why
I'm lazy - I won't keep a form going - but I do want to know where my time goes: am I wasting it, or compounding it?
Here's what actually changed for me: I'm already in an AI chat for hours a day. So logging isn't a new habit to build - it's one more sentence in a conversation I'm already having. Zero friction, because it rides a habit I already have - which is exactly why it sticks where timers and forms die in three days.
And the point isn't the log - it's compounding. Once you can see where the hours actually go, you can steer them toward the work that builds on itself. The skill does the grunt work (categorize, estimate, write the row), and when it's unsure it asks instead of guessing - a log that quietly invents facts is worse than none.
What it is
A Claude skill (a single SKILL.md of instructions) + your own Notion database. No server, no backend to deploy. Capture anywhere you have Claude or ChatGPT (phone / laptop / chat); your Notion is the source of truth (cloud, phone-native). Heads up: the skill / connector setup currently runs only on the paid tiers of Claude and ChatGPT.
Sister project: trading-ledger - the same method (your own Notion as source of truth + a skill that parses plain language + asks instead of guessing), applied to your trades: it makes you state your reason at the moment of entry.
Install
Step 0 - duplicate the Notion template (same for both forms): 🇬🇧 English · 🇨🇳 中文. One click; fields, views, and example rows included.
Then pick your form - both do the same thing, just a different surface:
| ⌨️ Terminal · Claude Code | 💬 Web · Claude.ai |
|---|---|
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Also works in ChatGPT (paid) - connect the Notion connector and paste these instructions into a Custom GPT. No skill upload, so a touch more setup. |
Where to click - Claude.ai & ChatGPT (each step red-boxed; the ChatGPT side needs a paid plan):
Claude Code commands (中文 → swap SKILL.md for SKILL.zh-CN.md):
git clone https://github.com/cruisekkk/time-ledger.git
mkdir -p ~/.claude/skills/time-ledger
cp time-ledger/SKILL.md ~/.claude/skills/time-ledger/SKILL.md
Either way - no id to paste. The skill finds your database by title (keep time-ledger / 时间账本 in it, and share just that one), reads its id, and writes the row - asking instead of guessing when it's unsure. (On Claude.ai the first write pops an approve prompt - Notion's write tools default to Needs approval - so it's expected, not a hang.)
Customize - want different categories or another language? Change the fields in your database, then mirror them in the skill's instructions (the select values must match).
Usage
- Just report: say what you did → the AI parses and writes it, batch-asking on anything uncertain.
- Batch reconcile: say "tidy up my time ledger" → the AI pulls every
待确认(to-confirm) row and asks you in one message, then fills them in. - See the breakdown: Notion's built-in calendar view + group-by-activity sum; or ask your AI to draw a chart on the spot.
Review it with your AI - no fixed dashboard. Ask "how did my week go - am I compounding?" and it generates the view live: bars, a compounding donut, a streak heatmap, a reading-vs-building ratio - whatever you ask for.
Honest limitations
- You have to actually report - it doesn't auto-track (on purpose; a tracker doesn't know why you spent the time).
- The
compounding / consuming / neutraltags are hand-rules today, not learned - a real engine is roadmap, not repo. - n=1: the author's daily driver since June 2026 - but still a sample size of one.
Design philosophy
From a larger personal project (inveself), one line: "You have to become a compounding person before you can be a good compounding investor." This ledger is the tool for that line - it honestly mirrors whether your hours compound (it once showed the author a week of reading:building ≈ 30:1).
FAQ
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Discussion
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