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BF dual-stream-architecture

Dual-stream event publishing combining Kafka for durability with Redis Pub/Sub for real-time delivery. Use when building event-driven systems needing both guaranteed delivery and low-latency updates. Triggers on dual stream, event publishing, Kafka Redis, real-time events, pub/sub, streaming architecture.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 1 340 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Dual-stream event publishing combining Kafka for durability with Redis Pub/Sub for real-time delivery.

As a process F 49/100 · Will not run — References files that are not bundled: ../../meta/realtime-dashboard/, ../websocket-hub-patterns/, ../../backend/service-layer-architecture/

GeneratorSoftware developmentData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
F
49/100
Will not run
References files that are not bundled: ../../meta/realtime-dashboard/, ../websocket-hub-patterns/, ../../backend/service-layer-architecture/
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • 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-ref reference to a missing file: ../../meta/realtime-dashboard/
  • warning missing-ref reference to a missing file: ../websocket-hub-patterns/
  • warning missing-ref reference to a missing file: ../../backend/service-layer-architecture/

Process rating: all ten parameters 49/100

Will not run. References files that are not bundled: ../../meta/realtime-dashboard/, ../websocket-hub-patterns/, ../../backend/service-layer-architecture/
  • 0Tools and files. 3 referenced file(s) missing: ../../meta/realtime-dashboard/, ../websocket-hub-patterns/, ../../backend/service-layer-architecture/
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 12 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1340 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 top-level sections: this looks like several domains in one skill

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 306: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 12 items
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.