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heath-ledger

AI Community
Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network
Domain
AI
Compatible agents
  • Claude Code
  • Cursor
  • Cline
  • Codex
  • Windsurf
  • Gemini CLI
  • +20
Trust score
88 / 100 · community maintained
Author / version / license
@diegosouzapw · no license declared
Token usage
Lean
Setup complexity
Guided setup
External API key
Required · Stripe
Operating systems
macOS · Linux · Windows
Runtime requirements
Node.js
Permissions
  • Read-only
  • Write / modify
Network behavior
External requests
Install commands
26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview heath-ledger.preview 
---
name: heath-ledger
description: AI bookkeeping agent for Mercury bank accounts. Pulls transactions, categorizes them (rule-based…
category: ai
runtime: Node.js
---

# heath-ledger output preview

## PART A: Task fit
- Use case: AI bookkeeping agent for Mercury bank accounts. Pulls transactions, categorizes them (rule-based + AI), and generates Excel workbooks with P&L, Balance Sheet, Cash Flow, and transaction detail. Use when the user wants to do bookkeeping, generate financial statements, categorize bank transactions, connect Mercury, or produce monthly/quarterly/annual books. Triggers on: bookkeeping, P&L, profit and loss, balance sheet, cash flow, financial statements, Mercury bank, categorize transactions, generate books, monthly close..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Quick Start / Setup Flow / Mercury API Key (Required)” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “AI bookkeeping agent for Mercury bank accounts. Pulls transactions, categorizes them (rule-based + AI), and generates Excel workbooks with P&L, Balance Sheet, Cash Flow, and transaction detail. Use when the user wants to do bookkeeping, generate financial statements, categorize bank transactions, connect Mercury, or produce monthly/quarterly/annual books. Triggers on: bookkeeping, P&L, profit and loss, balance sheet, cash flow, financial statements, Mercury bank, categorize transactions, generate books, monthly close.”.
- **02** When the source has headings, the agent prioritizes “Quick Start / Setup Flow / Mercury API Key (Required)” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; may access external network resources; requires Stripe API keys.

## Running Rules
- read files, write/modify files; may access external network resources; requires Stripe API keys.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.
Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

  • Core job: AI bookkeeping agent for Mercury bank accounts. Pulls transactions, categorizes them (rule-based + AI), and generates Excel work…
  • Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
  • Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

  • Structure: The skill is organized around “Quick Start”, “Setup Flow”, “Mercury API Key (Required)”, “Stripe API Key (Optional but Recommended)”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
  • Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
  • Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

  • Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
  • Invocation: Name heath-ledger directly; if the source includes slash commands, start with the command and then add task context.
  • Validation: Start small and check whether the result follows “Quick Start / Setup Flow / Mercury API Key (Required)” before expanding.

Boundaries And Review

  • Dependencies: Prepare Stripe API keys before running a full task.
  • Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
  • Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

Discussion

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