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Issue #129 Keep templates user-focused; AGENTS for contributors
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.github/ISSUE_TEMPLATE.md

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(Optional) When submitting an Issue, please consider using a "deep research" tool to sanity check your proposal. Then **before** submission, run your draft through a strong model with a prompt such as:
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> "Please review the AGENTS.md and README.md along with this draft Issue and check that it does not have any gaps — why it might be insufficient, incomplete, lacking a concrete example, duplicating prior issues or PRs, or not be aligned with the project goals or non‑goals."
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> "Please review README.md along with this draft Issue and check that it does not have any gaps — why it might be insufficient, incomplete, lacking a concrete example, duplicating prior issues or PRs, or not be aligned with the project goals or non‑goals."
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If you used an AI assistant while preparing this Issue, ensure it followed the contributor/agent workflow rules in `AGENTS.md`.
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(Optional) Please then attach both the prompt and the model's review to the bottom of this template under "Augmented Intelligence Review".
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.github/ISSUE_TEMPLATE/bug_report.md

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(Optional) When submitting a bug report, please consider using an AI assistant to help create a minimal test case that demonstrates the issue. Then **before** submission, run your bug description through a strong model with a prompt such as:
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> "Please review the AGENTS.md and README.md along with this bug report and check that it includes: a clear description of the problem, steps to reproduce, expected vs actual behavior, and a minimal test case that demonstrates the bug."
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> "Please review README.md along with this bug report and check that it includes: a clear description of the problem, steps to reproduce, expected vs actual behavior, and a minimal test case that demonstrates the bug."
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If you used an AI assistant while preparing this report, ensure it followed the contributor/agent workflow rules in `AGENTS.md`.
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(Optional) Please then attach both the prompt and the model's review to the bottom of this template under "Augmented Intelligence Review".
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.github/ISSUE_TEMPLATE/custom.md

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(Optional) When submitting this issue, please consider using an AI assistant to help analyze and articulate the problem. Then **before** submission, run your issue description through a strong model with a prompt such as:
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> "Please review the AGENTS.md and README.md along with this issue description and check that it: clearly explains the problem or request, provides sufficient context, includes relevant details, and aligns with project standards."
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> "Please review README.md along with this issue description and check that it: clearly explains the problem or request, provides sufficient context, includes relevant details, and aligns with project standards."
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(Optional) Please then attach both the prompt and the model's review to the bottom of this template under "Augmented Intelligence Review".
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If you used an AI assistant while preparing this issue, ensure it followed the contributor/agent workflow rules in `AGENTS.md`.
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(Optional) Please then attach both the prompt and the model's review to the bottom of this template under "Augmented Intelligence Review".
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.github/ISSUE_TEMPLATE/feature_request.md

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(Optional) When submitting a feature request, please consider using an AI assistant to validate your implementation approach. Then **before** submission, run your feature description through a strong model with a prompt such as:
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> "Please review the AGENTS.md and README.md along with this feature request and check that it: aligns with project goals, doesn't duplicate existing functionality, includes concrete use cases, and suggests a reasonable implementation approach."
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> "Please review README.md along with this feature request and check that it: aligns with project goals, doesn't duplicate existing functionality, includes concrete use cases, and suggests a reasonable implementation approach."
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If you used an AI assistant while preparing this request, ensure it followed the contributor/agent workflow rules in `AGENTS.md`.
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(Optional) Please then attach both the prompt and the model's review to the bottom of this template under "Augmented Intelligence Review".
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.github/pull_request_template.md

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(Optional) When submitting an PR, please consider using a "deep research" tool to sanity check your proposal. Then **before** submission, run your draft through a strong model with a prompt such as:
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(Optional) When submitting a PR, please consider using a "deep research" tool to sanity check your proposal. Then **before** submission, run your draft through a strong model with a prompt such as:
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> "Please review the AGENTS.md and README.md along with this draft PR and check that it does not have any gaps — why it might be insufficient, incomplete, lacking a concrete example, duplicating prior issues or PRs, or not be aligned with the project goals or non‑goals."
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> "Please review README.md along with this draft PR and check that it does not have any gaps — why it might be insufficient, incomplete, lacking a concrete example, duplicating prior issues or PRs, or not be aligned with the project goals or non‑goals."
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If you used an AI assistant while preparing this PR, ensure it followed the contributor/agent workflow rules in `AGENTS.md`.
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(Optional) Please then attach both the prompt and the model's review to the bottom of this template under "Augmented Intelligence Review".
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**(Optional) Augmented Intelligence Review**:
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*Both prompt and model out, asking a strong model to double-check your submission, from the perspective of a maintainer of this repo*
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AGENTS.md

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## Purpose & Scope
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- Operational guidance for human and AI agents working in this repository. This revision preserves all existing expectations while improving structure and wording in line with agents.md best practices.
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User-facing documentation lives in `README.md`. Keep this file focused on contributor/agent workflow, debugging, and coding standards.
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## Operating Principles
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- Follow the sequence plan → implement → verify; do not pivot without restating the plan.
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- Stop immediately on unexpected failures and ask before changing approach.
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Use `Json.toDisplayString(value, depth)` to render JSON fragments in error messages, and include relevant context like schema paths, actual vs expected values, and specific constraint violations.
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## JSON Compatibility Suite
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```bash
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# Build and run compatibility report
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mvn clean compile generate-test-resources -pl json-compatibility-suite
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mvn exec:java -pl json-compatibility-suite
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# Run JSON output (dogfoods the API)
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mvn exec:java -pl json-compatibility-suite -Dexec.args="--json"
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```
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See `README.md` for user-facing commands. When running locally as an agent, use the Maven wrapper described in this file.
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## Architecture Overview
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## Common Workflows
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### API Compatibility Testing
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1. Run the compatibility suite: `mvn exec:java -pl json-compatibility-suite`.
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2. Inspect reports for regressions relative to upstream expectations.
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3. Validate outcomes against the official JSON Test Suite.
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## Module Reference
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### json-java21
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- Main library delivering the core JSON API.
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- Maven coordinates: `io.github.simbo1905.json:json-java21:0.X.Y`.
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- Requires Java 21 or newer.
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### json-compatibility-suite
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- Automatically downloads the JSON Test Suite from GitHub.
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- Surfaces known vulnerabilities (for example, StackOverflowError under deep nesting).
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- Intended for education and testing, not production deployment.
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### json-java21-api-tracker
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- Tracks API evolution and compatibility changes.
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- Uses Java 24 preview features (`--enable-preview`).
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- Runner: `io.github.simbo1905.tracker.ApiTrackerRunner` compares the public JSON API (`jdk.sandbox.java.util.json`) with upstream `java.util.json`.
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- Workflow fetches upstream sources, parses both codebases with the Java compiler API, and reports matching/different/missing elements across modifiers, inheritance, methods, fields, and constructors.
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- Continuous integration prints the report daily. It does not fail or open issues on differences; to trigger notifications, either make the runner exit non-zero when `differentApi > 0` or parse the report and call `core.setFailed()` within CI.
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### json-java21-jtd (JTD Validator)
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- JSON Type Definition validator implementing RFC 8927 specification.
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- Provides eight mutually-exclusive schema forms for simple, predictable validation.
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- Uses stack-based validation with comprehensive error reporting.
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- Includes full RFC 8927 compliance test suite.
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Prefer linking to `README.md` for stable, user-facing workflows and module descriptions. Keep this file focused on agent execution details.
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#### Debugging Exhaustive Property Tests
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