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.
npx skills add mhylle/claude-skills-collection --skill strategic-compactgit clone --depth 1 https://github.com/mhylle/claude-skills-collectionWrote 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.
[](https://agentmods.dev/skills/mhylle/claude-skills-collection/strategic-compact)<a href="https://agentmods.dev/skills/mhylle/claude-skills-collection/strategic-compact"><img src="https://agentmods.dev/badge/skills/mhylle/claude-skills-collection/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.
<a href="https://agentmods.dev/skills/mhylle/claude-skills-collection/strategic-compact"><img src="https://agentmods.dev/badge/skills/mhylle/claude-skills-collection/strategic-compact.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 3 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- high Memory Poisoning · line 42 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00137 | $0.01600 |
| Opus 5 | $0.00068 | $0.00800 |
| Sonnet 5 | $0.00027 | $0.00320 |
| Haiku 4.5 | $0.00014 | $0.00160 |
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.
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Strategic Compact
Suggest context compaction at logical boundaries — not arbitrary token thresholds. Auto-compaction is a safety net; strategic compaction is a workflow optimization that makes compaction feel like a natural pause instead of an interruption.
Why strategic > automatic
Auto-compaction fires on simple thresholds (token count, time). That creates real problems:
- Mid-task disruption — auto-compact might fire while you're debugging, losing the mental model built up over many interactions.
- Context fragmentation — arbitrary cutoffs create artificial boundaries in session history.
- Lost continuity — "why" decisions get compacted away at random points rather than preserved at meaningful boundaries.
- Incomplete state — mid-implementation compaction can lose partially completed work.
Strategic compaction instead:
- Monitors for logical boundaries (task completion, phase transitions, successful commits).
- Considers semantic state (actively debugging vs. between tasks).
- Provides suggestions — never forces compaction.
- Integrates with
context-saverto preserve critical state first. - Respects workflow rhythm rather than imposing arbitrary limits.
Goal: compaction that feels like a natural pause, not an interruption.
When to use
Passive monitoring — via PreToolUse hook that attaches to every tool call, tracks counters, and evaluates boundaries. Hook setup → references/hook-setup.md.
Direct invocation:
/strategic-compact— check current session state and get a recommendation./strategic-compact status— view tool counts and threshold proximity./strategic-compact now— force a suggestion (auto-invokes context-saver first).
Trigger phrases: "should I compact", "when should I clear context", "getting long", "checkpoint", "context is getting big".
The core heuristic
Two questions:
- Has enough work happened that compaction is worthwhile? (weighted tool-call count vs. threshold)
- Is this moment a good place to compact? (logical boundary vs. mid-task)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 163 lines · 137 tokens per session scan A ad120f1fc8bc
strategic-compact is a skill published in the GitHub repository mhylle/claude-skills-collection (18 stars, last pushed 9d ago), licensed MIT. It adds 137 tokens to every session and 1,600 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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