An automation for syncing Toshl Finance data into local CSV or JSON files and creating monthly financial reports.

It is for syncing the current month or a selected month range, reconciling changes, and generating reports from Toshl account entries.

It keeps a local, trackable copy of finance data and compares new downloads with the previous state to identify discrepancies.

toshl — Skill for Claude Code by digital-stoic-org

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/digital-stoic-org/agent-skills

agentmods

npx agentmods add skills/digital-stoic-org/agent-skills/toshl

Made for: Claude Code.

Or install content, the plugin that ships this one along with the rest of its 7 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/toshl/github.svg)](https://agentmods.dev/skills/digital-stoic-org/agent-skills/toshl)

Your own site

<a href="https://agentmods.dev/skills/digital-stoic-org/agent-skills/toshl"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/toshl/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/digital-stoic-org/agent-skills/toshl"><img src="https://agentmods.dev/badge/skills/digital-stoic-org/agent-skills/toshl.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,189 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Excessive Agency · line 6
Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.

Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00019	$0.01189
Opus 5	$0.00010	$0.00594
Sonnet 5	$0.00004	$0.00238
Haiku 4.5	$0.00002	$0.00119

Measured 10d ago against content hash deee06ad74f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

toshl scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

content/skills/toshl/SKILL.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Toshl Financial Automation

Automate Toshl Finance data synchronization and monthly reporting with multi-entity financial strategy context (NS/DS/LW/VN + CCA extraction planning).

Data source: Toshl Finance API (via toshl MCP server) Cache: Local CSV/JSON in toshl/data/ (git-tracked) Reports: Markdown files in toshl/reports/

Commands

sync-data [start-month] [end-month]

Sync Toshl data to local CSV cache with reconciliation vs. prior state.

Usage:

/toshl sync-data                    # Current month MTD
/toshl sync-data 2026-03            # Single month
/toshl sync-data 2026-01 2026-04    # Inclusive month range

Implementation: Runs scripts/monthly_sync.py which calls the Toshl API directly (not via MCP — avoids token-limit spills). Stdlib only, no venv needed.

# Current month MTD
python3 toshl/scripts/monthly_sync.py --current

# Specific month
python3 toshl/scripts/monthly_sync.py 2026-03

# Range
python3 toshl/scripts/monthly_sync.py 2026-01 2026-04

# With reconcile report
python3 toshl/scripts/monthly_sync.py --current --json-report /tmp/reconcile.json

Script behavior:

Reads TOSHL_API_TOKEN from toshl/.env
Paginates /entries (per_page=200) for each month's date range
Resolves account/category/tag IDs against data/_{account,category,tag}_lookup.json
Writes data/{YYYY-MM}_entries.csv (denormalized, UTF-8, sorted date desc)
Reconciles: prints rows/sum before → after and delta per month
Idempotent — re-running the same month yields Δ=0

CSV format (denormalized, human-readable):

date,description,amount,currency,category,account,tags,type
2026-02-05,Groceries,-45.50,EUR,Food & Dining,Cash,shopping,expense
2026-02-10,Freelance Income,2500.00,EUR,Consulting,Cash,revenue,income

When to use MCP vs. this script:

Script (monthly_sync.py): for bulk backfill, monthly ritual, reconciliation. Always preferred for writing CSVs.
MCP tools (mcp__toshl__*): for live querying during analysis ("what did I spend on X?"). Never use for bulk export — token-limit spills on months >40 entries.

Read the full file on GitHub · 128 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

reference.md 3.6 KB

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

10d ago First seen · 128 lines · 19 tokens per session scan A deee06ad74f6

Subscribe to this mod's changes

toshl is a skill published in the GitHub repository digital-stoic-org/agent-skills (20 stars, last pushed 4d ago), licensed MIT. It adds 19 tokens to every session and 1,189 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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