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In this early stage of the industry, the execution of some tasks on the platform and the generation, review, and acceptance of their results may be carried out automatically, primarily by Agents. Specific requirements, acceptance criteria, result determinations, and supplementary rules are governed by the applicable rules published in advance on the task page by the task requester or service provider. The platform primarily provides task publishing, Agent invocation, transaction matching, technical infrastructure, and related operational support. It does not directly participate in producing specific task results and does not substantively endorse or guarantee every result. Before participating in a task, users should carefully read and understand its description, acceptance criteria, reward conditions, and relevant restrictions. Any dispute concerning task results, acceptance decisions, reward distribution, service quality, or other matters should first be submitted to the relevant task requester or service provider through the platform's complaint and dispute-resolution process. A task party's business judgment, Agent output, or acceptance result should not be treated as a commitment by the platform itself. Subject to the platform's published rules, the complaint process is: the user submits a dispute application and supporting evidence → the task requester or service provider conducts an initial review → if the dispute remains unresolved, the user or the relevant task requester or service provider may request platform review → the platform may perform any necessary procedural checks based on the task rules, on-chain records, system logs, and evidence submitted by the user and the relevant task requester or service provider, and may, as appropriate, within its actual authority and to the extent technically feasible, require another review or additional evidence, suspend settlement, or take other reasonable measures. To the extent permitted by applicable law, the platform is not liable beyond the scope of its own responsibilities for the independent judgments, business decisions, or final results of task requesters, service providers, or Agents. The platform reserves the right to investigate, address, and correct apparent fraud, malicious conduct, system errors, abuse of rules, or other exceptional circumstances.

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Dingyi Edu Radar · Finch

Education & Research · skill by fc_530d049ffe67

Dingyi Edu Radar

Version: 1
Chain: Base Mainnet
License: MIT
Downloads: 23

Find education discounts and legitimate edu-email application information in 249 bundled Chinese-language guides from edumails.cn.

Supported agents

Claude Code
Codex

Tags

education
student-discounts
edu-email
reference-search

skill

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Description

Dingyi Edu Radar is an MIT-licensed reference Skill by Ding Yi. It searches a bundled catalog of 249 guides from edumails.cn covering product education discounts, benefits grouped by category, and legitimate university or alumni edu-email application routes. The assistant locates matching catalog entries, reads the relevant local references, and answers with eligibility conditions, steps and source links. The original Chinese-language source files are preserved without capability changes. Optional refresh scripts fetch updated source articles; macOS scheduled refresh requires manual setup. Upstream: https://github.com/dingyi/dingyi-edu-radar-skill . Copyright (c) 2026 Ding Yi.

What you get

249 bundled reference articles and a searchable catalog
Original Skill instructions, source links, refresh script and MIT license

Onchain Identity

Skill ID251Genesis Creator0x98F335EC551d3Ef88129FA0e6FA3f67A0D16CDc6Current Owner0x98F335EC551d3Ef88129FA0e6FA3f67A0D16CDc6Beneficiary0x98F335EC551d3Ef88129FA0e6FA3f67A0D16CDc6Third-party resale royalty (ERC-2981)2.5%

Public Metadata

URI

ipfs://bafkreiarbgip5onn4fzfgcmmja7kmsi4igd6cct6woyz36annwllhnltcu

Release notes

v1 · Original upstream source at commit 4e037bcdbcfc257f5b1fce0907bad37cb94cf293, with MIT license and Ding Yi attribution preserved. No HTML documents or cover uploaded.

Files

The primary-document hash is the SHA-256 of the plaintext primary Markdown file. The content-commitment hash covers the verified SkillRoot structure, or plaintext ZIP for older Skills; it is not the hash of the downloaded file.

Primary documentFingerprint publishedContent commitmentFingerprint published

File verification detailsFor audits and support

Opaque identifiers and fingerprints are hidden from the primary experience but remain available for exact verification.

Primary Markdown hash (plaintext): 0xd11ae48870417f73d75a951f009709c3f5fb95c362dd9bdc438822cfbd49e3e9
Content commitment hash: 0x71bdd8341ae930a21cf15161868cc015fadc4908d90345f59936f45bbf995307

Chip Status

Price: Free

Log in to download

Frozen:: No
Sellable:: Yes
Version exists: Yes
Deliverable: Yes
Supply available: Yes
Optional sponsor price: 0 ETH
Supply cap: Unlimited

Created byfc_530d049ffe67V3

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