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 guanyang/open-agent-hub --skill self-managed-contextgit clone --depth 1 https://github.com/guanyang/open-agent-hubWrote 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/guanyang/open-agent-hub/self-managed-context)<a href="https://agentmods.dev/skills/guanyang/open-agent-hub/self-managed-context"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/self-managed-context/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/guanyang/open-agent-hub/self-managed-context"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/self-managed-context.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 | $0.00149 | $0.05042 |
| Opus 5.5 | $0.00060 | $0.02017 |
| Sonnet 5.5 | $0.00030 | $0.01008 |
| Haiku 4.5 | $0.00015 | $0.00504 |
Grade A, and why
self-managed-context 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 18d 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.
This is a copy
100% identical to self-managed-context — 0 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.
How it starts
The opening of the file, as written. The whole thing — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Managed Context
This skill covers agents that manage their own context window: the model, not the harness, decides what stays in the live context, what is compacted, what is evicted, and what is rewritten in place. The reference implementation is Context Language Models (CLMs), which mirror the editable part of the conversation into a file that the model edits with ordinary code tools, then re-parse that file into the next prompt. Applied zero-shot to existing models on a shared agent backbone, this matched or beat harness-scheduled and action-based context management on accuracy and compute across deep-research, terminal-coding, and multi-hour repository-optimization tasks (claim-self-managed-context-zero-shot-results, claim-self-managed-context-long-horizon-results).
The controlling trade-off: model control buys adaptivity (verbatim retention, surgical in-place updates, eviction on demand) and creates three problems the harness must absorb. Edits break prefix caching, so a badly placed edit can cost more compute than the tokens it frees. Models do not know how full their context is. And a model-writable context is a persistence channel for whatever the model writes into it, including instructions. Most of this skill is the harness contract that makes the first property worth the other three.
When to Activate
Activate this skill when:
- Giving a model write access to its own live context instead of compacting on a fixed schedule
- Designing a context-as-a-file protocol: turn headers, parse-back, pinned prefix, edit receipts
- An agent must keep exact values, update state in place, or evict offloaded material, and fixed summarization loses or duplicates it
- Pricing mid-context edits under prefix caching, or evaluating suffix cache reuse
- Budget readouts, tiered nudges, or rollback for an agent that times its own compaction
- Steering, evolving, or training a model's context-editing strategy
- Diagnosing a self-editing agent that never edits, wipes useful state, livelocks after overflow, or carries injected instructions in its own notes
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.
- 18d ago First seen · 277 lines · 149 tokens per session scan A 0b077da6d772
self-managed-context is a skill published in the GitHub repository guanyang/open-agent-hub (980 stars, last pushed yesterday), licensed MIT. It adds 149 tokens to every session and 5,042 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to self-managed-context, differing in 0 lines, and is treated as a copy.
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