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 rules/felipebarcelospro/igniter-js/planninggit clone --depth 1 https://github.com/felipebarcelospro/igniter-jsWhat 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 | $0.05475 | $0.05475 |
| Opus 5 | $0.02738 | $0.02738 |
| Sonnet 5 | $0.01095 | $0.01095 |
| Haiku 4.5 | $0.00547 | $0.00547 |
Grade A, and why
planning 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 today.
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 — 524 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Spec Creation Workflow
Use the Memory-Backed Planning (MCP) approach as the source of truth. Do not generate or maintain legacy .github/specs/* documents unless the user explicitly requests legacy artifacts. Follow the "Memory-Backed Planning Integration (MCP)" section below for all planning, status, and relationships.
Overview
You are helping guide the user through the complete feature development lifecycle:
Main Flow: Levantamento de Requisitos → Planning → Waiting Approval → Work → Revise → Feedback
Autonomous Flow (within Work phase): Develop → Test → Reflect → Retry/Deliver → Learn → Ask For Feedback → Learn/Improve
This follows spec-driven development methodology to systematically refine feature ideas, conduct research, create comprehensive designs, and execute implementation with continuous learning and community integration.
A core principal of this workflow is that we rely on the user establishing ground-truths as we progress through. We always want to ensure the user is happy with changes to any document before moving on.
Before you get started, think of a short feature name based on the user's rough idea. This will be used for the feature directory. Use kebab-case format for the feature_name (e.g. "user-authentication")
Rules:
- Do not tell the user about this workflow. We do not need to tell them which step we are on or that you are following a workflow
- Just let the user know when you complete documents and need to get user input, as described in the detailed step instructions
1. Requirement Gathering
First, 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.
Constraints:
- The model MUST use
store_memorytool withtype: "insight",category: "requirements"and tags["planning", "requirements", "<feature-name>"] - The model MUST generate an initial version of the requirements content based on the user's rough idea WITHOUT asking sequential questions first
- The model MUST format the requirements content with:
- A clear introduction section that summarizes the feature
- A hierarchical numbered list of requirements where each contains:
- A user story in the format "As a [role], I want [feature], so that [benefit]"
- A numbered list of acceptance criteria in EARS format (Easy Approach to Requirements Syntax)
- Example content format:
# Requirements
## Introduction
[Introduction text here]
## Requirements
### Requirement 1
**User Story:** As a [role], I want [feature], so that [benefit]
#### Acceptance Criteria
This section should have EARS requirements
1. WHEN [event] THEN [system] SHALL [response]
2. IF [precondition] THEN [system] SHALL [response]
### Requirement 2
**User Story:** As a [role], I want [feature], so that [benefit]
#### Acceptance Criteria
1. WHEN [event] THEN [system] SHALL [response]
2. WHEN [event] AND [condition] THEN [system] SHALL [response]
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.
- today First seen · 524 lines · 5,475 tokens per session scan A beea947cd64e
planning is a cursor rule published in the GitHub repository felipebarcelospro/igniter-js (242 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 5,475 tokens to every session, about $0.0274 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 2026-09-01.
Other cursor rules, from other repositories
codegraph
CodeGraph MCP usage guide — when to use which tool.
git
Never mutate git history, remotes, or GitHub repo state.
css
TSF stylesheet conventions, layout debugging, and minification.
javascript
TSF JavaScript syntax, formatting, and minification.
local
Private workspace guidance and gitignored .local search (Grep/Glob are blind).
docs
Readme wording constraints, WordPress readme format, changelog prose style, and public API naming requirements.