claude

session-efficiency

Token-efficient habits, per-task model and effort selection, session memory, docs-first discipline, autonomous execution, and structured work reports for Claude Code.

0 on GitHubby Arnav Shahv1.1.0MITupdated 6 days agoproductivity
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Plugin session-efficiency from marketplace engineering-standards-marketplace in shah-arnav3/eng_standards-marketplace-claudecode. Commands read from the repo's manifest — 6 days ago.

What it installs

Skills (6)

  • model-selection

    Choosing the right Claude model and effort level per task in Claude Code — for the main session, for subagents via frontmatter or the Agent tool's model parameter, and for skills — and avoiding the cache and quality costs of switching. Use when delegating work to a subagent, defining a subagent or s

  • plow-ahead

    Autonomous execution through ordinary ambiguity — turning routine questions into stated assumptions, choosing small reversible options, validating as you go, and stopping only for real blockers (missing credentials, destructive or outward-facing actions, decisions the user reserved). Use only when t

  • read-the-docs

    Docs-first discipline — reading current, authoritative documentation (local specs, official references, migration guides, SDK types) before writing code or answers that depend on an external API, library, CLI, cloud service, or fast-moving product behavior, instead of relying on memory. Use when add

  • session-memory

    Managing what Claude Code remembers within and across sessions — keeping CLAUDE.md and rules lean and scoped, maintaining auto memory (MEMORY.md and topic files), compacting at the right time with focus instructions, persisting state before compaction or /clear, handoff documents for multi-session w

  • token-efficiency

    Token-efficient working habits for Claude Code sessions — reading files narrowly, delegating broad searches to subagents, filtering command output, keeping the prompt cache warm, and trimming always-on context from skills, plugins, and MCP servers. Use when a task will read many files or produce lar

  • work-report

    A structured, detailed end-of-task report — results with verification evidence, actions taken, open findings, clarifications (assumptions made and questions to confirm), and next steps split between the user and Claude Code. Use when finishing or pausing multi-step work such as implementing a featur

View source on GitHub

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