docs: move project description to README, point AGENTS.md to it
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AGENTS.md
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AGENTS.md
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@ -1,24 +1,24 @@
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# Timesheets — Agent Guide
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## Project overview
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> **Read `README.md` first** for a full description of the project, its
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> subcommands, config file format, and Joplin notebook structure.
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A Python CLI tool that parses markdown pipe-delimited timesheet tables and
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exports them to CSV for import into Odoo (or similar tools). It also supports
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a human-readable summary view and can fetch notes directly from Joplin.
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### Package layout
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## Package layout
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```
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timesheets/
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├── pyproject.toml # package metadata, entry point, dev dependencies
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├── pyproject.toml
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├── README.md
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├── AGENTS.md
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├── timesheets.example.toml
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└── src/timesheets/
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├── cli.py # argument parsing, main() entry point
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├── parser.py # markdown table parsing, aggregation, date filtering
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├── projects.py # project_map.json loading and key resolution
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├── output.py # CSV writing and summary printing
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├── output.py # CSV writing, summary, stories, and status printing
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├── config.py # TOML config file loading and key extraction
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├── joplin.py # Joplin API integration (notebook traversal, note fetching)
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├── status.py # day/week status calculations
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└── utils.py # shared low-level helpers (duration parsing, formatting, etc.)
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```
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@ -31,7 +31,8 @@ tests/
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├── test_projects.py
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├── test_config.py
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├── test_output.py
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└── test_joplin.py
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├── test_joplin.py
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└── test_status.py
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```
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---
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@ -51,81 +52,6 @@ Do **not** use `pip` or `python` directly.
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---
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## CLI usage
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The CLI has two subcommands: `summary` and `csv`. Both accept the same arguments.
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```sh
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# Human-readable summary for today (from Joplin)
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uv run timesheets summary --joplin
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# Human-readable summary for a specific day
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uv run timesheets summary 2026-05-22 --joplin
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uv run timesheets summary yesterday --joplin
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uv run timesheets summary 3 days ago --joplin
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# Export today's entries as CSV to stdout
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uv run timesheets csv --joplin
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# Export to a file
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uv run timesheets csv --joplin -o output.csv
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# Use a local markdown file instead of Joplin
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uv run timesheets summary --input timesheet.md
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uv run timesheets csv --input timesheet.md -o output.csv
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# Read from stdin
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cat timesheet.md | uv run timesheets csv --input -
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# Specify a day (positional, accepts YYYY-MM-DD, MM-DD, or DD-MM; - or / separator)
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uv run timesheets csv 2026-05-22 --input input.md
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uv run timesheets csv 05-22 --input input.md
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# Use a specific project map file
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uv run timesheets csv --input input.md --map /path/to/project_map.json
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# Fetch entries for a specific day from Joplin
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uv run timesheets csv 2026-05-22 --joplin --token your_token
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```
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`project_map.json` is auto-discovered in the current working directory if
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`--map` is not provided.
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---
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## Config file
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Create `timesheets.toml` in your working directory (or pass `--config /path/to/file.toml`):
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```toml
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[joplin]
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token = "your_api_token_here"
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[projects]
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map = "/path/to/project_map.json"
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```
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Priority order for each value: **CLI flag > config file > environment variable / default**.
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---
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## Joplin notebook structure
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The `--joplin` flag expects the following notebook hierarchy in Joplin:
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```
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Work/
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└── Timesheets/
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└── YYYY/
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└── YYYY - WNN/ ← notebook per week
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└── YYYY - WNN ← note with the same title as the notebook
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```
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The note body contains one markdown table per day, each preceded by a heading
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of the form `# <weekday> - YYYY-MM-DD`.
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---
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## Testing
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The test suite uses **pytest** with **pytest-cov** for coverage reporting.
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@ -165,3 +91,71 @@ uv run pytest tests/test_parser.py::TestParseTable::test_empty_input
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5. Joplin integration tests in `test_joplin.py` must mock `ClientApi` — do not
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require a live Joplin instance.
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# Development Guidelines
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# CLAUDE.md
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Behavioral guidelines to reduce common LLM coding mistakes. Merge with project-specific instructions as needed.
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**Tradeoff:** These guidelines bias toward caution over speed. For trivial tasks, use judgment.
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## 1. Think Before Coding
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**Don't assume. Don't hide confusion. Surface tradeoffs.**
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Before implementing:
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- State your assumptions explicitly. If uncertain, ask.
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- If multiple interpretations exist, present them - don't pick silently.
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- If a simpler approach exists, say so. Push back when warranted.
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- If something is unclear, stop. Name what's confusing. Ask.
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## 2. Simplicity First
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**Minimum code that solves the problem. Nothing speculative.**
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- No features beyond what was asked.
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- No abstractions for single-use code.
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- No "flexibility" or "configurability" that wasn't requested.
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- No error handling for impossible scenarios.
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- If you write 200 lines and it could be 50, rewrite it.
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Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.
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## 3. Surgical Changes
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**Touch only what you must. Clean up only your own mess.**
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When editing existing code:
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- Don't "improve" adjacent code, comments, or formatting.
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- Don't refactor things that aren't broken.
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- Match existing style, even if you'd do it differently.
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- If you notice unrelated dead code, mention it - don't delete it.
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When your changes create orphans:
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- Remove imports/variables/functions that YOUR changes made unused.
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- Don't remove pre-existing dead code unless asked.
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The test: Every changed line should trace directly to the user's request.
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## 4. Goal-Driven Execution
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**Define success criteria. Loop until verified.**
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Transform tasks into verifiable goals:
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- "Add validation" → "Write tests for invalid inputs, then make them pass"
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- "Fix the bug" → "Write a test that reproduces it, then make it pass"
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- "Refactor X" → "Ensure tests pass before and after"
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For multi-step tasks, state a brief plan:
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```
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1. [Step] → verify: [check]
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2. [Step] → verify: [check]
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3. [Step] → verify: [check]
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```
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Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.
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---
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**These guidelines are working if:** fewer unnecessary changes in diffs, fewer rewrites due to overcomplication, and clarifying questions come before implementation rather than after mistakes.
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