AF context-engineering
Comprehensive context engineering guidance for AI agent systems. Routes to specialized sub-skills for production agent work. Use when the user asks to: "optimize context", "reduce token costs", "context compression", "summarize conversation history", "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "implement memory", "build memory system", "offload context to files", "use filesystem for agent memory", "debug agent failure", "diagnose context problems", "fix lost-in-middle", "build agent tools", "design agent tools", "evaluate agent performance", "build test framework", "implement LLM-as-judge", "understand context", "explain context windows", "build background agent", "implement BDI architecture", "start an LLM project", or any discussion of context degradation, attention patterns, multi-agent coordination, or production agent architecture.
Comprehensive context engineering guidance for AI agent systems.
As a process F 43/100 · Will not run — References files that are not bundled: references/context-engineering-skills/
How to improve
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/context-engineering-skills/
Process rating: all ten parameters 43/100
- 0Tools and files. 1 referenced file(s) missing: references/context-engineering-skills/
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (context-engineering) differs from the folder (levineam-context-engineering)
- 65Failures and branches. 3 branches
- 70When it triggers. States when to use, but not when not to
- 100Steps. 6 steps
- 100Execution cost. Instruction body is 991 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 894: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 24 example trigger phrases
- +4Structure: 5 headings
- +3Step-by-step instructions: 6 items
- +4Has examples (7 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.