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 yeaight7/agent-powerups --skill strategic-context-compactiongit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/strategic-context-compaction)<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/strategic-context-compaction"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/strategic-context-compaction/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/yeaight7/agent-powerups/strategic-context-compaction"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/strategic-context-compaction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00059 | $0.00944 |
| Opus 5.5 | $0.00024 | $0.00378 |
| Sonnet 5.5 | $0.00012 | $0.00189 |
| Haiku 4.5 | $0.00006 | $0.00094 |
Grade A, and why
strategic-context-compaction 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 1mo 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
-
Decide whether to compact by transition. Use the boundary table; default to NOT compacting mid-work.
Transition Compact? Reason Research -- Planning Yes Research context is bulky; the plan is the distilled output Planning -- Implementation Yes Plan is saved in tasks/files; context is free to reset Implementation -- Testing Maybe Keep if tests reference recent code; compact if switching focus area Debugging -- Next feature Yes Debug traces pollute unrelated work Mid-implementation No Losing file paths, variable names, partial state is costly After a failed approach Yes Clear dead-end reasoning before trying a new approach -
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
-
Know what survives versus what is lost. Anything in the Lost column must be persisted in step 2 first.
Survives Lost CLAUDE.md / AGENTS.md instructions Intermediate reasoning Task list (TodoWrite) File contents read in session Files on disk Tool call history Git state Verbally stated preferences Memory files Multi-step conversation context
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.
- 1mo ago First seen · 80 lines · 59 tokens per session scan A 3e3293f94859
strategic-context-compaction is a skill published in the GitHub repository yeaight7/agent-powerups (8 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 59 tokens to every session and 944 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-14.
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