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 skills/rtazima/claude-proj-blueprint/context-engineeringnpx skills add rtazima/claude-proj-blueprint --skill context-engineeringgit clone --depth 1 https://github.com/rtazima/claude-proj-blueprintWrote 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/rtazima/claude-proj-blueprint/context-engineering)<a href="https://agentmods.dev/skills/rtazima/claude-proj-blueprint/context-engineering"><img src="https://agentmods.dev/badge/skills/rtazima/claude-proj-blueprint/context-engineering.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 | $0.00077 | $0.01664 |
| Opus 5 | $0.00039 | $0.00832 |
| Sonnet 5 | $0.00015 | $0.00333 |
| Haiku 4.5 | $0.00008 | $0.00166 |
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 5d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Engineering
Proactively manage what goes into the context window. More context is NOT better — the right context at the right time is better. This skill teaches techniques to keep context lean, focused, and effective.
The reactive context-guard hook warns when context is bloated (50+ tool calls).
This skill prevents it from getting there in the first place.
Rules
- Target <2,000 lines per task — if a task requires reading more, split it
- Load on demand — don't read files "just in case". Read when you need them
- Forget aggressively — once a file is understood, stop re-reading it
- Prefer Grep over Read — search for what you need instead of reading entire files
- One concern per session — avoid mixing unrelated tasks in the same conversation
- Summarize, don't accumulate — after analyzing multiple files, synthesize findings into a brief summary instead of carrying all raw content
Context hierarchy
What to load first, in priority order:
| Priority | Source | Why |
|---|---|---|
| 1 | CLAUDE.md |
Project rules, conventions, commands — always relevant |
| 2 | Spec modules (docs/specs/) |
Only the ones active for this task |
| 3 | The specific files being changed | Direct context for the work |
| 4 | Test files for changed code | Verify behavior expectations |
| 5 | Error output / logs | Only when debugging |
| 6 | Conversation history | Degrades over time — prefer files as source of truth |
Techniques
1. Task decomposition
Before starting a large task, split it into independent sub-tasks:
Task: "Implement user authentication"
→ Sub-task 1: Design auth API (read: PRD, API spec)
→ Sub-task 2: Implement auth middleware (read: framework docs, existing middleware)
→ Sub-task 3: Add auth tests (read: test patterns, middleware code)
→ Sub-task 4: Update docs (read: CLAUDE.md, existing docs)
Each sub-task has its own minimal context set.
2. Strategic file reading
BAD: Read entire src/ to "understand the codebase"
GOOD: Grep for the function name, read only the relevant file + its test
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.
- 5d ago First seen · 156 lines · 77 tokens per session scan A 6abf1be85bc9
context-engineering is a skill published in the GitHub repository rtazima/claude-proj-blueprint (20 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 1,664 once invoked, about $0.0004 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 skills, from other repositories
project
Create or maintain an Architecture Studio project — initialize its record bundle, remember sourced facts, capture or supersede decisions, inspect project status, or migrate a 1.x PROJECT.md. Use when the user says “set up the project,” “remember this,” “we decided,” asks about project context, or runs /as:project.
init-workspace-documentation
Skill "init-workspace-documentation" from griddynamics/rosetta, covering agent memory.md, agent memory, preventive rules, what worked and what failed.
decision-memory
Use when planning, designing, reviewing, or changing code in a repository that keeps ADRs (usually docs/adr) — to load the decisions that already govern the work, check a plan or diff against them, or record a new decision. Also use when a choice feels already-settled and you cannot find where it was settled.
memory-continuity
Preserves cross-session continuity with deterministic MEMORY.md, index.md, and snapshot handoffs under .agentic/memories/.
plan-memory-index
Maintains concise indexed memory entries for applied plans under .agentic/memories/ with clear boundaries between memory and plan sources. Memory retrieval is prioritized before loading historical plan files.
self-improving-agent
Log learnings, errors, and corrections to .learnings/ for continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects the agent, (3) A knowledge gap is identified, (4) A better approach is found. Captures corrections, insights, errors, and feature requests; promotes broadly…