bunny-graphql

Engineering Community
Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network
Domain
Engineering
Compatible agents
  • Claude Code
  • Cursor
  • Cline
  • Codex
  • Windsurf
  • Gemini CLI
  • +20
Trust score
88 / 100 · community maintained
Author / version / license
@tomevault-io · no license declared
Token usage
Heavy
Setup complexity
Manual integration
External API key
Required · Vendor-specific
Operating systems
macOS · Linux · Windows
Runtime requirements
Node.js · Python
Permissions
  • Read-only
  • Write / modify
  • Env read
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 bunny-graphql.preview
---
name: bunny-graphql
description: Direct GraphQL API integration with Bunny — the subscription billing and management platform. Co…
category: engineering
runtime: Node.js / Python
---

# bunny-graphql output preview

## PART A: Task fit
- Use case: Direct GraphQL API integration with Bunny — the subscription billing and management platform. Covers the endpoint URL (https://<subdomain>.bunny.com/graphql), Bearer-token authentication, OAuth2 client-credentials flow with automatic token refresh, pagination via Relay-style connections, error response shape, and the most common queries and mutations for accounts, subscriptions, quotes, invoices, and payments. Use when calling Bunny's GraphQL API from a language without an official SDK (Go, Python, Rust, Elixir, PHP, Java, .NET, etc.), when the Node or Ruby SDKs don't cover an operation you need, or when you need to understand the raw request / response shape. For Node prefer the `bunny-node-sdk` skill; for Ruby prefer the `bunny-ruby-sdk` skill. Use when this capability is needed..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Credential safety / Endpoint / Authentication” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Direct GraphQL API integration with Bunny — the subscription billing and management platform. Covers the endpoint URL (https://<subdomain>.bunny.com/graphql), Bearer-token authentication, OAuth2 client-credentials flow with automatic token refresh, pagination via Relay-style connections, error response shape, and the most common queries and mutations for accounts, subscriptions, quotes, invoices, and payments. Use when calling Bunny's GraphQL API from a language without an official SDK (Go, Python, Rust, Elixir, PHP, Java, .NET, etc.), when the Node or Ruby SDKs don't cover an operation you need, or when you need to understand the raw request / response shape. For Node prefer the `bunny-node-sdk` skill; for Ruby prefer the `bunny-ruby-sdk` skill. Use when this capability is needed.”.
- **02** When the source has headings, the agent prioritizes “Credential safety / Endpoint / Authentication” 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, read environment variables; may access external network resources; requires Vendor-specific API keys.

## Running Rules
- read files, write/modify files, read environment variables; may access external network resources; requires Vendor-specific 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: Direct GraphQL API integration with Bunny — the subscription billing and management platform. Covers the endpoint URL (https://<…
  • 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 “Credential safety”, “Endpoint”, “Authentication”, “Access token (simplest)”, 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 bunny-graphql 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 “Credential safety / Endpoint / Authentication” before expanding.

Boundaries And Review

  • Dependencies: Prepare Vendor-specific API keys before running a full task.
  • Permissions: Declared permissions include read / write / env-read; 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

Powered by GitHub Discussions. Sign in with GitHub to comment, react, or subscribe.