Borrowing it
Nothing to install: this file belongs to Yashwanth-pilli/ILLIP. 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/Yashwanth-pilli/ILLIP/main/AGENTS.mdgit clone --depth 1 https://github.com/Yashwanth-pilli/ILLIPWrote 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/instructions/yashwanth-pilli/illip/agents-md)<a href="https://agentmods.dev/instructions/yashwanth-pilli/illip/agents-md"><img src="https://agentmods.dev/badge/instructions/yashwanth-pilli/illip/agents-md.svg" alt="Measured on agentmods" 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 | $0.01392 | $0.01392 |
| Opus 5 | $0.00696 | $0.00696 |
| Sonnet 5 | $0.00278 | $0.00278 |
| Haiku 4.5 | $0.00139 | $0.00139 |
Grade A, and why
ILLIP AGENTS.md 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.
How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ILLIP AI - Agent Framework Documentation
Overview
ILLIP AI uses a specialized agent framework with five complementary agents that work together to support autonomous development workflows.
Agents
1. Planner Agent
Role: Task decomposition and planning
- Analyzes high-level goals
- Breaks them into actionable tasks
- Identifies dependencies
- Estimates effort
- Creates execution plans
Trigger: POST /api/agents/planner/execute
Example:
Input: "Build user authentication system"
Output: Plan with tasks for login, signup, password reset, token management
2. Builder Agent
Role: Code generation and implementation
- Receives task descriptions
- Generates code implementations
- Follows project conventions
- Includes documentation
- Writes production-ready code
Trigger: POST /api/agents/builder/execute
Example:
Input: "Create user login endpoint"
Output: Python FastAPI route with auth logic, error handling, tests
3. Reviewer Agent
Role: Quality assurance and review
- Reviews code for quality
- Checks for security issues
- Verifies standards compliance
- Provides improvement suggestions
- Creates review reports
Trigger: POST /api/agents/reviewer/execute
Example:
Input: "Review the login endpoint code"
Output: Report with quality assessment, security review, recommendations
4. Tester Agent
Role: Testing and validation
- Designs test cases
- Executes tests
- Reports results
- Identifies bugs
- Verifies requirements
Trigger: POST /api/agents/tester/execute
Example:
Input: "Test the login endpoint"
Output: Test results, coverage report, identified issues
5. Memory Agent
Role: Knowledge and context management
- Stores decisions and learnings
- Retrieves context when needed
- Searches knowledge base
- Manages conversation memory
- Maintains audit trail
Trigger: POST /api/agents/memory/execute
Example:
Input: "store:user_auth_patterns"
Output: Knowledge stored for future reference
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 · 272 lines · 1,392 tokens per session scan A 6ba0e443aee2
ILLIP AGENTS.md is an instructions file published in the GitHub repository Yashwanth-pilli/ILLIP (24 stars, last pushed 1mo ago), licensed MIT. It adds 1,392 tokens to every session, about $0.0070 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 2026-08-30.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.