cap-context-engineering

Category: Tools & Productivity | Uploader: bikeread | Downloads: 0 | Version: v1.0（Latest）

Design what context an agent sees, when it sees it, and how that context is compressed or retrieved.

Changelog: Source: GitHub https://github.com/bikeread/promethos

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Current level: tree/main/skills/cap-context-engineering/

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- 📄 worked-example.md 2.3 KB
📄 SKILL.md 2.8 KB

SKILL.md

---
name: cap-context-engineering
description: Design what context an agent sees, when it sees it, and how that context is compressed or retrieved.
when_to_use: >-
  Use when deciding what information to load into the agent, what to defer, and how to control context growth. Examples: "design the context strategy", "what should the agent read", "how do we avoid context bloat"
---

# Goal
Give the agent the minimum useful context needed to perform well without
overloading it or hiding critical information.

## Inputs
- Agent task shape
- Available sources of truth
- Context window and retrieval constraints

## Non-Goals
- Designing long-term memory policy in full
- Dumping every possibly relevant file into context

## Workflow

### 1. Define the task loop the agent must sustain
Describe the recurring loop the agent is performing so context choices can be
judged against actual operational needs.
**Success criteria**: Context design is anchored to a concrete task loop rather
than a vague idea of "more context is better."

### 2. Identify the immediate working set
Choose the small set of facts, files, instructions, and state that must be
present at the start of the loop.
**Success criteria**: The initial context is justified, bounded, and clearly
more important than deferred material.

### 3. Separate eager, deferred, and retrieved information
Classify what should always be loaded, what can be discovered on demand, and
what should stay out of the active context entirely.
**Success criteria**: The strategy distinguishes mandatory context from optional
or expensive context.

### 4. Define source-of-truth and compression rules
State which representations are authoritative, when summaries may replace raw
material, and when the agent must re-open original sources.
**Success criteria**: Compression never silently becomes a substitute for the
real source of truth.

### 5. Define refresh and reset behavior
Specify when context should be trimmed, refreshed, re-retrieved, or rebuilt from
clean state.
**Success criteria**: The agent has a plan for long-running usefulness rather
than unchecked context accumulation.

## Output Contract
A context strategy covering:
- the operating loop,
- the initial working set,
- eager vs deferred vs retrieved information,
- source-of-truth precedence,
- compression and refresh rules.

## Escalation
Pause when:
- critical information cannot be separated from optional information,
- the design assumes the model will remember everything indefinitely,
- summaries are replacing raw sources without a re-open rule,
- retrieval latency or context budget makes the proposed strategy unrealistic.

## Common Failure Modes
- Front-loading too much context
- Treating summaries as if they were canonical truth
- Compressing away important state
- Treating retrieval as a replacement for clear boundaries

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cap-context-engineering

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