Stats
Actions
Tags
From craftwork-context-engineering
Routes user intents to context engineering skills for creating agent instructions, debugging failures, evaluating context impact, gap analysis, or documentation. Entry point for general agent context tasks.
How this skill is triggered — by the user, by Claude, or both
Slash command
/craftwork-context-engineering:context-engineering-orchestratorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**This skill routes — it does not reason.** Read the user's intent, match it to an entry point below, then execute that skill's SKILL.md.
This skill routes — it does not reason. Read the user's intent, match it to an entry point below, then execute that skill's SKILL.md.
Read what the user wants to do and match it to the closest entry below. If ambiguous, ask one clarifying question.
| User wants to... | Start with | Then |
|---|---|---|
| Find what context is missing from a codebase | context-gap-analyzer | → agent-instruction-forge if gaps need rules |
| Create or improve agent instruction files (CLAUDE.md, .cursorrules, etc.) | agent-instruction-forge | → rule-quality-evaluator → edd |
| Score or audit existing agent instructions | rule-quality-evaluator | → agent-instruction-forge if score is low |
| Measure whether agent context actually helps | context-eval | → agent-instruction-forge if regression found |
| Iterate on a context harness with tests | edd | → context-eval for measurement |
| Design what goes into a context window | context-cartography | → context-gap-analyzer to validate coverage |
| Debug why an agent is failing / ignoring instructions | context-debugging | → context-gap-analyzer or edd based on findings |
| Extract business logic or domain rules from code | business-logic-extractor | → llms-txt-generator or agent-instruction-forge |
| Process a large document for LLM consumption | deep-document-processor | → llms-txt-generator |
| Generate an llms.txt or LLM-friendly reference | llms-txt-generator | → context-compressor if over budget |
| Optimize / compress context to fit a token budget | context-compressor | → context-eval to verify compressed context works |
| Find false positives in AI-generated tests | test-challenger | → edd if better assertions needed |
skills/[skill-name]/SKILL.mdDo NOT auto-execute the "Then" skill. Propose it:
Based on [what the skill produced], a natural next step would be:
→ [skill-name]: [1-sentence reason]
Want me to continue with that, or is this what you needed?
Multiple follow-ups → list as options. User chooses; orchestrator never chains automatically.
These are the most common multi-skill sequences in this group:
Full context engineering lifecycle:
context-gap-analyzer → agent-instruction-forge → rule-quality-evaluator → context-eval → edd
Use when building agent context from scratch or doing a comprehensive audit.
Creating agent instructions:
context-gap-analyzer → agent-instruction-forge → rule-quality-evaluator → edd
Use when the goal is specifically to create or improve instruction files.
Debugging agent failures:
context-debugging → context-gap-analyzer → agent-instruction-forge → edd
Use when an agent is behaving incorrectly and you suspect the context layer.
Building documentation:
business-logic-extractor → llms-txt-generator
deep-document-processor → llms-txt-generator
Use when creating LLM-consumable reference material.
| Skill | Purpose |
|---|---|
context-gap-analyzer | Find implicit context missing from a codebase |
agent-instruction-forge | Create instruction rules for coding agents |
rule-quality-evaluator | Score rules on Seven Properties, detect redundancies |
context-cartography | Design what goes into an agent's context window |
context-debugging | Diagnose agent failures originating in the context layer |
context-eval | Measure whether context changes improve outcomes |
edd | Eval-Driven Development — TDD for context |
llms-txt-generator | Generate token-efficient context documents |
deep-document-processor | Multi-pass reading of large documents |
business-logic-extractor | Extract domain rules from code |
context-compressor | Maximize signal-per-token under a finite budget |
test-challenger | Find false positives in AI-generated tests |
Fetches up-to-date documentation from Context7 for libraries and frameworks like React, Next.js, Prisma. Use for setup questions, API references, and code examples.
Applies a firm's KYC/AML rules grid to parsed onboarding records: assigns risk rating, checks required documents, outputs rule outcomes with citations, and routes for escalation.
Generates daily or weekly digests of activity from connected sources (chat, email, docs, tasks, CRM), highlighting action items, decisions, mentions, and project updates.
npx claudepluginhub andurilcode/craftwork --plugin craftwork-context-engineering