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clawkk

Cache Layer

by clawkk · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
131
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Install in OpenClaw
/install cache-layer
Description
Cache layers, TTLs, invalidation, and consistency. Use when speeding reads or debugging stale data.
README (SKILL.md)

Cache Layer

Structured guidance for cache layers (TTLs, invalidation, consistency): confirm triggers, propose the stages below, and adapt if the user wants a lighter pass.

When to Offer This Workflow

Trigger conditions:

  • User mentions caching, cache invalidation, or closely related work
  • They want a structured workflow rather than ad-hoc tips
  • They are preparing a review, rollout, or stakeholder communication

Initial offer: Explain the four stages briefly and ask whether to follow this workflow or work freeform. If they decline, continue in their preferred style.

Workflow Stages

Stage 1: Clarify context & goals

Anchor on what to cache and TTL rationale. Ask what success looks like, constraints, and what must not break. Capture unknowns early.

Stage 2: Design or plan the approach

Translate goals into a concrete plan around invalidation patterns. Compare alternatives and explicit trade-offs; avoid implicit assumptions.

Stage 3: Implement, validate, and harden

Execute with verification loops tied to consistency and thundering herds. Prefer small steps, measurable checks, and rollback points where risk is high.

Stage 4: Operate, communicate, and iterate

Close the loop with monitoring hit rate and staleness: monitoring, documentation, stakeholder updates, and lessons learned for the next cycle.

Checklist Before Completion

  • Goals and constraints are explicit for cache layers
  • Risks and trade-offs are stated, not hand-waved
  • Verification steps match the change’s impact (tests, canary, peer review)
  • Operational follow-through is covered (monitoring, docs, owners)

Tips for Effective Guidance

  • Be procedural: stage-by-stage, with clear exit criteria
  • Ask for missing context (environment, scale, deadlines) before prescribing
  • Prefer checklists and concrete examples over generic platitudes
  • If the user declines the workflow, switch to freeform help without lecturing

Handling Deviations

  • If the user wants to skip a stage: confirm and continue with what they need.
  • If context is missing: ask targeted questions before strong recommendations.
  • Prefer concrete examples, trade-offs, and verification steps over generic advice.

Quality Bar

  • Each recommendation should be actionable (what to do next).
  • Call out failure modes relevant to cache layers (security, scale, UX, or ops).
  • Keep tone direct and respectful of the user’s time.
Usage Guidance
This skill is a pure guidance/workflow helper and appears safe and coherent with its purpose. Because it is instruction-only, it won't execute code or access secrets by itself — still: review any recommendations before applying them, avoid pasting secrets into prompts, and if you want to prevent autonomous invocation, disable model invocation for this skill in your agent settings.
Capability Analysis
Type: OpenClaw Skill Name: cache-layer Version: 1.0.0 The skill bundle contains only metadata and structured markdown instructions (SKILL.md) for guiding a user through cache layer design and implementation. It lacks any executable code, network requests, or malicious prompt injection, focusing entirely on architectural best practices like TTL management and cache invalidation.
Capability Assessment
Purpose & Capability
Name and description match the SKILL.md content: it provides a staged workflow for cache design, implementation, and operation. There are no unrelated permissions, binaries, or env vars requested.
Instruction Scope
Runtime instructions are procedural guidance and questions for the user; they do not instruct the agent to read files, access credentials, call external endpoints, or perform broad system operations.
Install Mechanism
No install spec and no code files — instruction-only skill. Nothing is written to disk or downloaded during install.
Credentials
The skill requests no environment variables, credentials, or config paths; requested access is proportional (none) to the stated task.
Persistence & Privilege
always is false and the skill is user-invocable. It does not request permanent presence or elevated privileges beyond normal skill invocation.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install cache-layer
  3. After installation, invoke the skill by name or use /cache-layer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release providing a structured, stage-based workflow for cache layer guidance. - Introduces a four-stage workflow: clarify context, plan approach, implement & validate, operate & iterate. - Includes trigger conditions to identify when to offer structured cache advice. - Provides a completion checklist to ensure thoroughness and explicitness. - Offers guidance on adapting the workflow to user preferences (structured vs freeform). - Emphasizes actionable, stage-by-stage recommendations with concrete examples and trade-off discussions.
Metadata
Slug cache-layer
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Cache Layer?

Cache layers, TTLs, invalidation, and consistency. Use when speeding reads or debugging stale data. It is an AI Agent Skill for Claude Code / OpenClaw, with 131 downloads so far.

How do I install Cache Layer?

Run "/install cache-layer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Cache Layer free?

Yes, Cache Layer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Cache Layer support?

Cache Layer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Cache Layer?

It is built and maintained by clawkk (@clawkk); the current version is v1.0.0.

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