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 ychampion/cskill-agents --skill turn-scoped-memory-prefetch-with-disposalgit clone --depth 1 https://github.com/ychampion/cskill-agentsWrote 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/ychampion/cskill-agents/turn-scoped-memory-prefetch-with-disposal)<a href="https://agentmods.dev/skills/ychampion/cskill-agents/turn-scoped-memory-prefetch-with-disposal"><img src="https://agentmods.dev/badge/skills/ychampion/cskill-agents/turn-scoped-memory-prefetch-with-disposal/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/ychampion/cskill-agents/turn-scoped-memory-prefetch-with-disposal"><img src="https://agentmods.dev/badge/skills/ychampion/cskill-agents/turn-scoped-memory-prefetch-with-disposal.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 | $0.00035 | $0.00507 |
| Opus 5 | $0.00017 | $0.00253 |
| Sonnet 5 | $0.00007 | $0.00101 |
| Haiku 4.5 | $0.00003 | $0.00051 |
Grade A, and why
turn-scoped-memory-prefetch-with-disposal 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 9d 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 — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL: Turn-Scoped Memory Prefetch with Disposal
Domain: context-management Trigger: When a turn needs contextual memory attachments but the main loop must stay streaming and reuse previous read state. Source Pattern: Distilled from reviewed session memory, compaction, and context-budgeting implementations.
Core Method
Launch a memory prefetch exactly once at the start of the turn and keep its handle alive while the main loop streams. Each loop iteration should check whether the prefetch has completed without blocking on it; if not, continue streaming and check again later. When the prefetch is ready, deduplicate the returned attachments against what the session has already read, emit the new attachments once, and mark the handle as consumed so later iterations do not re-send them. Dispose of the handle automatically when the turn ends, aborts, or transitions so no background work leaks across turns.
Key Rules
- Start the prefetch before the streaming loop begins and store its handle with the turn state so it cannot accidentally restart on subsequent iterations.
- Never block the main loop on the prefetch; poll readiness and continue streaming until the memory data is ready.
- Before adding attachments to the turn output, dedupe them against the cumulative read file state (or equivalent) so repeated memory hits from earlier iterations are skipped.
- After emitting attachments, set a consumed flag so downstream iterations skip re-emitting and the core method clearly signals it already produced this batch.
- Ensure the handle is disposed automatically when the generator exits, even when the turn aborts or transitions, to avoid leaked async work and to emit consistent telemetry.
Example Application
If you build a new agent that reads documents for each user question, start a prefetch before streaming the model response, monitor the handle each loop, and only yield the resolved memories once so the UI can display them without delaying the primary response funnel.
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.
- 9d ago First seen · 30 lines · 35 tokens per session scan A aba508b0260c
turn-scoped-memory-prefetch-with-disposal is a skill published in the GitHub repository ychampion/cskill-agents (36 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 507 once invoked, about $0.0002 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 2026-09-03.
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