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 skills add sampleXbro/agentsmesh --skill context-engineeringgit clone --depth 1 https://github.com/sampleXbro/agentsmeshWrote 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/skills/samplexbro/agentsmesh/context-engineering)<a href="https://agentmods.dev/skills/samplexbro/agentsmesh/context-engineering"><img src="https://agentmods.dev/badge/skills/samplexbro/agentsmesh/context-engineering/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/skills/samplexbro/agentsmesh/context-engineering"><img src="https://agentmods.dev/badge/skills/samplexbro/agentsmesh/context-engineering.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 | $0.00043 | $0.02341 |
| Opus 5.5 | $0.00017 | $0.00936 |
| Sonnet 5.5 | $0.00009 | $0.00468 |
| Haiku 4.5 | $0.00004 | $0.00234 |
Grade A, and why
context-engineering 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.
This is a copy
100% identical to context-engineering — 67 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Engineering
Overview
Feed agents the right information at the right time. Context is the single biggest lever for agent output quality — too little and the agent hallucinates, too much and it loses focus. Context engineering is the practice of deliberately curating what the agent sees, when it sees it, and how it's structured.
When to Use
- Starting a new coding session
- Agent output quality is declining (wrong patterns, hallucinated APIs, ignoring conventions)
- Switching between different parts of a codebase
- Setting up a new project for AI-assisted development
- The agent is not following project conventions
The Context Hierarchy
Structure context from most persistent to most transient:
┌─────────────────────────────────────┐
│ 1. Rules Files (CLAUDE.md, etc.) │ ← Always loaded, project-wide
├─────────────────────────────────────┤
│ 2. Spec / Architecture Docs │ ← Loaded per feature/session
├─────────────────────────────────────┤
│ 3. Relevant Source Files │ ← Loaded per task
├─────────────────────────────────────┤
│ 4. Error Output / Test Results │ ← Loaded per iteration
├─────────────────────────────────────┤
│ 5. Conversation History │ ← Accumulates, compacts
└─────────────────────────────────────┘
Level 1: Rules Files
Create a rules file that persists across sessions. This is the highest-leverage context you can provide.
CLAUDE.md (for Claude Code):
# Project: [Name]
## Tech Stack
- React 18, TypeScript 5, Vite, Tailwind CSS 4
- Node.js 22, Express, PostgreSQL, Prisma
## Commands
- Build: `npm run build`
- Test: `npm test`
- Lint: `npm run lint --fix`
- Dev: `npm run dev`
- Type check: `npx tsc --noEmit`
## Code Conventions
- Functional components with hooks (no class components)
- Named exports (no default exports)
- colocate tests next to source: `Button.tsx` → `Button.test.tsx`
- Use `cn()` utility for conditional classNames
- Error boundaries at route level
## Boundaries
- Never commit .env files or secrets
- Never add dependencies without checking bundle size impact
- Ask before modifying database schema
- Always run tests before committing
## Patterns
[One short example of a well-written component in your style]
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 · 289 lines · 43 tokens per session scan A a2b776874ffe
context-engineering is a skill published in the GitHub repository sampleXbro/agentsmesh (25 stars, last pushed 26d ago), licensed MIT. It adds 43 tokens to every session and 2,341 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to context-engineering, differing in 67 lines, and is treated as a copy.
Other skills, from other repositories
shared-agents-knowledge
Sync and use the shared-agents repo (team skills, rules + learnings). Use at session start, when loading team knowledge, searching learnings, or when the user mentions shared-agents, shared learnings, or team knowledge.
agent-memory
Recall earlier conversations from the user's other AI tools (Claude Code, Claude Desktop, Codex, Cursor, Gemini CLI, Antigravity, Devin), and search the files of the projects they indexed. Use before asking about or assuming a project's history, when the user refers to a prior decision, discussion or fix ("as we…
loredex-curate
Write a Start-Here brief for a project or a recent session's findings, and flag stale/duplicate/orphaned notes. Use when the user says "curate my dex/research", "where do I start", "make sense of this project", or just finished a session that produced several markdown files and wants a handoff.
loredex-mcp
Set up or explain the loredex MCP server — live dex access (search, read, handoffs, product state, safe writes) for any MCP-compatible agent. Use when the user wants agents to query the dex mid-task, asks to "connect the dex to Cursor/Codex/an agent", or asks what the loredex MCP tools do.
loredex-init
Set up loredex for the current project — creates/registers the dex and writes AGENTS.md/CLAUDE.md/.cursor rule conventions. Use when the user says "set up loredex", "init loredex", or wants to start tracking this project's research in a dex.
loredex-route
Process the dex's inbox/ plus any new frontmattered files in the current project right now. Use when the user says "route my findings", "file what's pending", or wants a routing pass forced immediately instead of waiting for the automatic Stop hook.