Borrowing it
Nothing to install: this file belongs to stevenflyai/llm-wiki-web. 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/stevenflyai/llm-wiki-web/main/.claude/commands/new-feature.mdgit clone --depth 1 https://github.com/stevenflyai/llm-wiki-webWrote 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/stevenflyai/llm-wiki-web/new-feature)<a href="https://agentmods.dev/commands/stevenflyai/llm-wiki-web/new-feature"><img src="https://agentmods.dev/badge/commands/stevenflyai/llm-wiki-web/new-feature/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/stevenflyai/llm-wiki-web/new-feature"><img src="https://agentmods.dev/badge/commands/stevenflyai/llm-wiki-web/new-feature.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 | $0.00000 | $0.00450 |
| Opus 5 | $0.00000 | $0.00225 |
| Sonnet 5 | $0.00000 | $0.00090 |
| Haiku 4.5 | $0.00000 | $0.00045 |
Grade A, and why
new-feature 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 8d 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.
What it actually says
/new-feature — 启动新功能的标准流程
You are starting a new feature for llm-wiki-web.
Your job in this session is ONLY to produce a SPEC. Do NOT write any code.
Step 1: Read context
Read these files in order:
docs/dev/CLAUDE-DEV.md— development contractDECISIONS.md— architecture decisions you must respectBACKLOG.md— existing ideasdocs/specs/_TEMPLATE.md— the SPEC template you'll use
Step 2: Identify the feature
Ask the user:
- "Which BACKLOG item are we promoting? Or is this a fresh idea?"
- If fresh, suggest adding it to BACKLOG first.
Step 3: Interview the user
Use the AskUserQuestion tool to dig into:
- Problem — what pain triggered this?
- Goals & Non-Goals — what's in, what's out
- Provider compatibility — which LLM providers must this work with?
- Wiki schema impact — does this change frontmatter / INDEX / LOG / new dirs?
- Failure modes — what can go wrong?
- Test strategy — how do we verify?
- Open questions — alternatives, trade-offs
Do not ask obvious questions. Dig into the hard parts. Keep interviewing until there are zero Open Questions.
Step 4: Write the SPEC
- Copy
docs/specs/_TEMPLATE.mdtodocs/specs/draft/<feature-slug>.md - Fill in every section
- Slug should be 2-4 kebab-case words
- Set Status to "Draft"
Step 5: End the session
Tell the user:
SPEC drafted at
docs/specs/draft/<slug>.md. Review it. If approved, rungit mvtoapproved/then start a fresh session for planning. Do NOT have me implement in this same session — context should be clean.
Do not generate PLAN.md. Do not write code. End here.
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.
- 8d ago First seen · 51 lines · 0 tokens per session scan A 475683373d39
new-feature is a command published in the GitHub repository stevenflyai/llm-wiki-web (19 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 450 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 2026-08-30.
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.