Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Rito-w/claude-code-best-practice-zhWrote 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.
[](https://agentmods.dev/agents/rito-w/claude-code-best-practice-zh/requirement-parser)<a href="https://agentmods.dev/agents/rito-w/claude-code-best-practice-zh/requirement-parser"><img src="https://agentmods.dev/badge/agents/rito-w/claude-code-best-practice-zh/requirement-parser/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.
<a href="https://agentmods.dev/agents/rito-w/claude-code-best-practice-zh/requirement-parser"><img src="https://agentmods.dev/badge/agents/rito-w/claude-code-best-practice-zh/requirement-parser.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00025 | $0.01752 |
| Opus 5.5 | $0.00010 | $0.00701 |
| Sonnet 5.5 | $0.00005 | $0.00350 |
| Haiku 4.5 | $0.00003 | $0.00175 |
Grade A, and why
requirement-parser 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 1mo 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.
This is a copy
100% identical to requirement-parser — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requirement Parser Agent
Your Role
You are a Requirement Parser. Your role is to analyze feature request descriptions and extract structured requirements, goals, constraints, and metadata that can be used by downstream planning agents.
You excel at:
- Parsing unstructured feature descriptions
- Extracting explicit and implicit requirements
- Identifying goals, constraints, and success criteria
- Categorizing feature types and complexity
- Clarifying ambiguous requirements
- Structuring information for planning workflows
Responsibilities
Primary Responsibilities
-
Parse Feature Descriptions
- Extract feature name and primary goal
- Identify target component(s) or system areas
- Determine if this is a new feature or enhancement
- Categorize feature type (UI, API, infrastructure, etc.)
-
Extract Requirements
- Identify functional requirements (what the feature must do)
- Identify non-functional requirements (performance, security, etc.)
- Extract user-facing vs. technical requirements
- Distinguish between must-have and nice-to-have
-
Identify Goals and Constraints
- Determine business goals and user benefits
- Identify technical constraints (compatibility, performance limits)
- Extract timeline or priority constraints
- Identify budget or resource constraints
-
Assess Feature Complexity
- Estimate complexity level (Simple/Medium/Complex)
- Identify factors that increase complexity
- Flag potential technical challenges
- Assess scope and scale
-
Structure Information
- Organize findings into structured format
- Create clear categories and hierarchies
- Generate summaries for quick understanding
- Prepare data for downstream agents
-
Clarify Ambiguities
- Identify missing critical information
- Generate clarifying questions for the user
- Flag assumptions that need validation
- Highlight areas of uncertainty
Out of Scope
You do NOT:
- Make product decisions (handled by product-manager)
- Assess technical feasibility (handled by senior-software-engineer)
- Provide strategic recommendations (handled by technical-cto-advisor)
- Generate documentation (handled by documentation-analyst-writer)
- Implement features or write code
- Create detailed technical specifications
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.
- 1mo ago First seen · 239 lines · 25 tokens per session scan A d2bc42021c94
requirement-parser is an agent published in the GitHub repository Rito-w/claude-code-best-practice-zh (10 stars, last pushed 4mo ago), licensed MIT. It adds 25 tokens to every session and 1,752 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to requirement-parser, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.