Borrowing it
Nothing to install: this file belongs to reinhardhq/claude-code-spec-boilerplate. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/reinhardhq/claude-code-spec-boilerplate/main/.claude/commands/kiro:spec-requirements.mdgit clone --depth 1 https://github.com/reinhardhq/claude-code-spec-boilerplateWrote 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/commands/reinhardhq/claude-code-spec-boilerplate/kiro-spec-requirements)<a href="https://agentmods.dev/commands/reinhardhq/claude-code-spec-boilerplate/kiro-spec-requirements"><img src="https://agentmods.dev/badge/commands/reinhardhq/claude-code-spec-boilerplate/kiro-spec-requirements/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/commands/reinhardhq/claude-code-spec-boilerplate/kiro-spec-requirements"><img src="https://agentmods.dev/badge/commands/reinhardhq/claude-code-spec-boilerplate/kiro-spec-requirements.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 | $0.00006 | $0.01491 |
| Opus 5 | $0.00003 | $0.00745 |
| Sonnet 5 | $0.00001 | $0.00298 |
| Haiku 4.5 | $0.00001 | $0.00149 |
Grade A, and why
kiro:spec-requirements 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requirements Generation
Generate comprehensive requirements for feature: $ARGUMENTS
Context Validation
Steering Context
- Architecture context: @.kiro/steering/structure.md
- Technical constraints: @.kiro/steering/tech.md
- Product context: @.kiro/steering/product.md
Existing Spec Context
- Current spec directory: !
ls -la .kiro/specs/$ARGUMENTS/ - Current requirements: @.kiro/specs/$ARGUMENTS/requirements.md
- Spec metadata: @.kiro/specs/$ARGUMENTS/spec.json
Task: Generate Initial Requirements
Generate an initial set of requirements in EARS format based on the feature idea, then iterate with the user to refine them until they are complete and accurate.
Don't focus on code exploration in this phase. Instead, just focus on writing requirements which will later be turned into a design.
Requirements Generation Guidelines
- Focus on Core Functionality: Start with the essential features from the user's idea
- Use EARS Format: All acceptance criteria must use proper EARS syntax
- No Sequential Questions: Generate initial version first, then iterate based on user feedback
- Keep It Manageable: Create a solid foundation that can be expanded through user review
1. EARS Format Requirements
EARS (Easy Approach to Requirements Syntax) is the mandatory format for acceptance criteria:
Primary EARS Patterns:
- WHEN [event/condition] THEN [system] SHALL [response]
- IF [precondition/state] THEN [system] SHALL [response]
- WHILE [ongoing condition] THE SYSTEM SHALL [continuous behavior]
- WHERE [location/context] THE SYSTEM SHALL [contextual behavior]
Combined Patterns:
- WHEN [event] AND [additional condition] THEN [system] SHALL [response]
- IF [condition] AND [additional condition] THEN [system] SHALL [response]
2. Requirements Hierarchy and Granularity
Structure Requirements with Clear Hierarchy:
# Requirements Document
├── Introduction (feature overview)
├── Requirements
│ ├── Requirement 1 (Major Feature Area)
│ │ ├── User Story (high-level need)
│ │ └── Acceptance Criteria (detailed EARS)
│ │ ├── Happy path scenarios
│ │ ├── Edge cases and error conditions
│ │ ├── User experience considerations
│ │ └── Technical constraints
│ ├── Requirement 2 (Next Feature Area)
│ └── ...
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.
- 12d ago First seen · 178 lines · 6 tokens per session scan A 65ea45ff432a
kiro:spec-requirements is a command published in the GitHub repository reinhardhq/claude-code-spec-boilerplate (2 stars, last pushed 1y ago), licensed MIT. It adds 6 tokens to every session and 1,491 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.