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.
npx agentmods add commands/kaze-jp/kusa/spec-initgit clone --depth 1 https://github.com/kaze-jp/kusaWhat 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 | $0.00000 | $0.00572 |
| Opus 5 | $0.00000 | $0.00286 |
| Sonnet 5 | $0.00000 | $0.00114 |
| Haiku 4.5 | $0.00000 | $0.00057 |
Grade A, and why
spec-init scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Initialize Feature Spec
Initialize a new feature specification directory and generate initial requirements.
Usage
/kiro:spec-init <feature-name>
Instructions
-
Worktree guard — Before anything else, check if you are working in a git worktree (not on the main/master branch). If you are on the main branch, stop and create a worktree first using the
superpowers:using-git-worktreesskill orgit worktree add. Do NOT proceed with spec initialization until you are in an isolated worktree. -
Read product context from
.ao/steering/product.mdif it exists. Use this to understand the product vision, target users, and strategic goals. -
Create the spec directory at
.kiro/specs/$FEATURE_NAME/. -
Gather feature information by asking the user:
- What is the feature's purpose?
- Who are the target users?
- What problem does it solve?
- Are there any known constraints?
-
Generate
requirements-init.mdin the spec directory with the following structure:
# Feature: <feature-name>
## Overview
<Brief description of the feature and its purpose>
## Product Context
<Relevant context from product.md>
## Initial Requirements
### Functional Requirements
<List requirements using EARS format>
### Non-Functional Requirements
<Performance, security, accessibility requirements using EARS format>
### Constraints
<Known constraints and limitations>
### Assumptions
<Assumptions made during requirements gathering>
### Open Questions
<Questions that need answers before proceeding>
-
Apply EARS format for all requirements:
- Ubiquitous: "The shall "
- Event-driven: "When , the shall "
- State-driven: "While , the shall "
- Optional: "Where , the shall "
- Unwanted: "If , the shall "
-
Confirm with the user that the initial requirements capture their intent before finalizing.
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.
- 2d ago First seen · 74 lines · 0 tokens per session scan A f1f880a3d984
spec-init is a command published in the GitHub repository kaze-jp/kusa (2 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 572 tokens. 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
git
Git operations with intelligent commit messages and workflow optimization.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.