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/kubev2v/forklift-console-pluginWrote 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/rules/kubev2v/forklift-console-plugin/feature-development)<a href="https://agentmods.dev/rules/kubev2v/forklift-console-plugin/feature-development"><img src="https://agentmods.dev/badge/rules/kubev2v/forklift-console-plugin/feature-development/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/rules/kubev2v/forklift-console-plugin/feature-development"><img src="https://agentmods.dev/badge/rules/kubev2v/forklift-console-plugin/feature-development.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 | $0.00010 | $0.01344 |
| Opus 5.5 | $0.00004 | $0.00538 |
| Sonnet 5.5 | $0.00002 | $0.00269 |
| Haiku 4.5 | $0.00001 | $0.00134 |
Grade A, and why
feature-development 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.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Development Workflow
Invoke with: "start a new feature", "work on MTV-XXX end to end", "full development workflow"
This is the complete workflow from picking up a Jira ticket to submitting a PR.
1. Workflow Overview
1. PICK UP TICKET
"Start working on MTV-1885"
Fetch ticket, understand requirements, plan approach
2. PLAN IMPLEMENTATION
"Help me plan the implementation"
Identify files to modify, components to create
3. IMPLEMENT
"Create the component", "Add the feature"
Write code following project standards (AGENTS.md)
4. TEST
"Test my changes", "Add unit tests"
Unit tests, interactive testing with Playwright
5. REVIEW
"Review my code"
Multi-perspective review (dev, UX, QE, security, Forklift expert)
6. PREPARE PR
"Prepare this for PR"
Quality checks, PR description, update Jira
2. Phase 1: Pick Up Ticket
Get the Ticket
"Start working on MTV-1885"
I will:
- Fetch ticket details from Jira
- Summarize requirements - what needs to be built
- Identify acceptance criteria - definition of done
- Check dependencies - blockers, related tickets
Understand the Context
- Epic/parent story
- Related tickets and comments
- Attached mockups or designs
3. Phase 2: Plan Implementation
Identify Code Changes
"Help me plan how to implement this"
I will:
- Find relevant existing code - similar components, utilities
- Identify files to modify - which components are affected
- Suggest new files needed - new components, hooks, utils
- Recommend approach - how to structure the solution
Consider Architecture
- Does this fit existing patterns?
- Should this be a reusable component?
- What's the impact on other features?
- Which provider types are affected?
4. Phase 3: Implement
Create Components
Following new-component.mdc workflow:
- Proper folder structure
- TypeScript types (using
type, notinterface) - SCSS styles with BEM
- Translation support (
useForkliftTranslation) - Accessibility requirements
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 · 237 lines · 10 tokens per session scan A aadadad0957f
feature-development is a cursor rule published in the GitHub repository kubev2v/forklift-console-plugin (11 stars, last pushed today), licensed Apache-2.0. It adds 10 tokens to every session and 1,344 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-30.
Other cursor rules, from other repositories
rebase-only-merged-agents
When rebasing after a merge, only rebase the agents whose branches you just merged. Do not rebase agents that are still running.
iris
GitHub operations specialist — branches, pull requests, issues, releases, tags. Called by zeus after review. Never pushes or merges without explicit human approval. Integrates with VS Code GitHub Pull Requests extension.
git-workflow
Rules for git operations, commit strategy, and GitHub CLI usage.
release-checklist
What to update with each code change or version release.
git-workflow
Git commit format and PR process - conventional commits.
branching-merging-strategy
This is a set of instructions to the AI Assistant for branching and merging strategy.