agentsclimarketplace

Strategic context compaction

Skill yeaight7/agent-powerups/plugins/dev-vitals/skills/strategic-context-compaction

Use when deciding whether to compact agent context -- the window is filling up, you are about to switch from one phase to another (research, planning, implementation, debugging), a failed approach left dead-end reasoning, or a previous mid-task compaction lost critical state.From its SKILL.md

Install
npx -y skills add yeaight7/agent-powerups --skill strategic-context-compaction

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.3 KB, 882 tokens by cl100k_base, as published. Nobody here has run it

Purpose

Compact at logical boundaries to preserve high-value context while clearing noise. Arbitrary or mid-task compaction loses critical state -- file paths, variable names, partial reasoning -- that is expensive to reconstruct.

When to Use

  • The context window is filling and you are at a phase boundary (research, planning, implementation, debugging)
  • A failed approach left dead-end reasoning that pollutes the next attempt
  • You are starting a conceptually distinct task in the same session
  • A prior mid-task compaction dropped state you then had to rebuild

Inputs

  • The current session state and which phase transition is approaching
  • Knowledge of what is already saved durably (task list, files, git, memory) versus only in conversation

Workflow

  1. Decide whether to compact by transition. Use the boundary table; default to NOT compacting mid-work.

    TransitionCompact?Reason
    Research -- PlanningYesResearch context is bulky; the plan is the distilled output
    Planning -- ImplementationYesPlan is saved in tasks/files; context is free to reset
    Implementation -- TestingMaybeKeep if tests reference recent code; compact if switching focus area
    Debugging -- Next featureYesDebug traces pollute unrelated work
    Mid-implementationNoLosing file paths, variable names, partial state is costly
    After a failed approachYesClear dead-end reasoning before trying a new approach
  2. Save anything you cannot reconstruct cheaply before compacting.

    • Write the plan to a task list or file before compacting after research
    • Commit or stash work-in-progress code before compacting after debugging
    • Note key file paths in the next prompt if they will be needed again
  3. Know what survives versus what is lost. Anything in the Lost column must be persisted in step 2 first.

    SurvivesLost
    CLAUDE.md / AGENTS.md instructionsIntermediate reasoning
    Task list (TodoWrite)File contents read in session
    Files on diskTool call history
    Git stateVerbally stated preferences
    Memory filesMulti-step conversation context
  4. Compact with an intent-carrying summary prompt, then restore.

    • Do not compact to "clean up" during active multi-file implementation
    • Pass forward intent, e.g. /compact -- now implementing auth middleware per plan
    • After compaction, re-read the task list or plan file to restore intent

Output

  • A compaction decision (do it now / wait until the next boundary) with the reason
  • A pre-compaction save of any non-reconstructible state (plan file, commit/stash, noted paths)
  • A summary prompt that carries intent into the cleared context

Token Awareness

  • Each loaded skill adds 1-5K tokens to context; load skills on demand, not at session start
  • CLAUDE.md / AGENTS.md are always loaded -- keep them lean
  • Duplicate instructions (root config plus plugin skill) are the most common waste

Verification

  • The chosen action matches the transition table -- no compaction during active multi-file implementation
  • Everything in the Lost column that is still needed was persisted (file, commit/stash, or next prompt) before compacting
  • The compact prompt carries forward intent rather than clearing blindly
  • After compaction, the task list or plan file was re-read to restore intent

Failure Modes

  • Mid-task compaction — compacting during active multi-file work and losing paths, variable names, and partial state that must then be rebuilt.
  • Compacting before saving — clearing context while the plan, WIP code, or key paths live only in conversation and not on disk or in tasks.
  • Blind compaction — using /compact with no intent summary, so the cleared session has no direction and re-derives the goal.
  • Skipping the restore step — not re-reading the task list or plan after compaction, then drifting from the original intent.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most memory context skills give in 882 tokens

Counted across 754 of the 1,056 authors here whose files we hold, read 2026-09-06

  • Preserve existing content structurein 15 of 754, across 9 files
  • Front-load the leading wordin 14 of 754, across 10 files
  • Update existing entries instead of duplicatingin 14 of 754, across 7 files
  • Keep CLAUDE.md under one hundred linesin 14 of 754, across 12 files
  • Read CLAUDE.md at the project rootin 14 of 754
  • Keep each meaning in a single source of truthin 12 of 754, across 8 files
  • Redact sensitive information before committingin 11 of 754, across 4 files
  • Scan for all CLAUDE.md filesin 11 of 754, across 7 files
  • Use frontmatter for metadata on filesin 10 of 754, across 3 files
  • Repeat user interactions 10 timesin 10 of 754, across 4 files
  • Write the CLAUDE.md file into the target folderin 10 of 754, across 8 files
  • Use memlab to process snapshotsin 9 of 754, across 3 files

Said here and by no other author read

  • Default to not compacting mid-work
  • Compact with an intent-carrying summary prompt
  • Re-read the task list after compaction

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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