strategic-compact

strategic-compact is a skill for Claude Code from huuanh20/awesome-ai-agent-skills. It costs 27 tokens per session (1,072 once invoked), scanned A, a copy of strategic-compact, MIT.

A workflow aid that suggests when to manually shorten the conversation context during long coding sessions. Context is the information an AI assistant keeps from earlier messages and tool calls.

In plain words
What is it for?
Choosing sensible pause points between research, implementation, testing, milestones, or unrelated tasks in a long session.
Why use it?
It helps avoid losing important details when automatic shortening happens in the middle of a task or when the conversation becomes too large.

Skill for Claude Code

Written for Claude Code: PreToolUse hook event. Also seen: reads .claude/ paths; mentions CLAUDE.md; names the TodoWrite tool.

Good fit Choosing sensible pause points between research, implementation, testing, milestones, or unrelated tasks in a long session.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/huuanh20/awesome-ai-agent-skills/strategic-compact
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add huuanh20/awesome-ai-agent-skills --skill strategic-compact
Clone the repo
git clone --depth 1 https://github.com/huuanh20/awesome-ai-agent-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for strategic-compact

README.md
[![agentmods](https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/strategic-compact/github.svg)](https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/strategic-compact)
Your own site
<a href="https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/strategic-compact"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/strategic-compact/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for strategic-compact

Your own site · 80×15
<a href="https://agentmods.dev/skills/huuanh20/awesome-ai-agent-skills/strategic-compact"><img src="https://agentmods.dev/badge/skills/huuanh20/awesome-ai-agent-skills/strategic-compact.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,072 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 75% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.01072
Opus 5 $0.00014 $0.00536
Sonnet 5 $0.00005 $0.00214
Haiku 4.5 $0.00003 $0.00107

Measured 12d ago against content hash 6cc33c111404, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

strategic-compact scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

75% identical to strategic-compact — 99 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/strategic-compact/SKILL.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Strategic Compact Skill

Suggests manual /compact at strategic points in your workflow rather than relying on arbitrary auto-compaction.

When to Activate

  • Running long sessions that approach context limits (200K+ tokens)
  • Working on multi-phase tasks (research → plan → implement → test)
  • Switching between unrelated tasks within the same session
  • After completing a major milestone and starting new work
  • When responses slow down or become less coherent (context pressure)

Why Strategic Compaction?

Auto-compaction triggers at arbitrary points:

  • Often mid-task, losing important context
  • No awareness of logical task boundaries
  • Can interrupt complex multi-step operations

Strategic compaction at logical boundaries:

  • After exploration, before execution — Compact research context, keep implementation plan
  • After completing a milestone — Fresh start for next phase
  • Before major context shifts — Clear exploration context before different task

How It Works

The suggest-compact.js script runs on PreToolUse (Edit/Write) and:

  1. Tracks tool calls — Counts tool invocations in session
  2. Threshold detection — Suggests at configurable threshold (default: 50 calls)
  3. Periodic reminders — Reminds every 25 calls after threshold

Configuration

Environment variables:

  • COMPACT_THRESHOLD — Tool calls before first suggestion (default: 50)

Compaction Decision Guide

Use this table to decide when to compact:

Phase Transition Compact? Why
Research → Planning Yes Research context is bulky; plan is the distilled output
Planning → Implementation Yes Plan is in TodoWrite or a file; free up context for code
Implementation → Testing Maybe Keep if tests reference recent code; compact if switching focus
Debugging → Next feature Yes Debug traces pollute context for unrelated work
Mid-implementation No Losing variable names, file paths, and partial state is costly
After a failed approach Yes Clear the dead-end reasoning before trying a new approach

Read the full file on GitHub · 119 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 119 lines · 27 tokens per session scan A 6cc33c111404

Subscribe to this mod's changes

strategic-compact is a skill published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 1mo ago), licensed MIT. It adds 27 tokens to every session and 1,072 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 75% identical to strategic-compact, differing in 99 lines, and is treated as a copy.

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