Borrowing it
Nothing to install: this file belongs to tjmustard/Hypergraph-Coding-Agent-Framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tjmustard/Hypergraph-Coding-Agent-Framework/main/.agents/skills/hyper-refresh-memory/SKILL.mdgit clone --depth 1 https://github.com/tjmustard/Hypergraph-Coding-Agent-FrameworkWrote 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/tjmustard/hypergraph-coding-agent-framework/hyper-refresh-memory)<a href="https://agentmods.dev/skills/tjmustard/hypergraph-coding-agent-framework/hyper-refresh-memory"><img src="https://agentmods.dev/badge/skills/tjmustard/hypergraph-coding-agent-framework/hyper-refresh-memory/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/tjmustard/hypergraph-coding-agent-framework/hyper-refresh-memory"><img src="https://agentmods.dev/badge/skills/tjmustard/hypergraph-coding-agent-framework/hyper-refresh-memory.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 | $0.00048 | $0.00556 |
| Opus 5.5 | $0.00019 | $0.00222 |
| Sonnet 5.5 | $0.00010 | $0.00111 |
| Haiku 4.5 | $0.00005 | $0.00056 |
Grade A, and why
refresh-memory 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 2mo 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Refresh Memory
This skill rebuilds the agent's mental model of the project by reading deterministic state, exploring the actual codebase, and updating the heuristic memory files to reflect current reality.
When to use this skill
- When starting a new session after a significant gap in development.
- When the agent's responses seem to reference outdated architecture or patterns.
- When the user explicitly runs
/hyper-refresh-memory. - After major refactors that may have drifted from documented patterns.
How to use it
-
Read Baseline State
- Read the deterministic state:
spec/compiled/architecture.yml(the Hypergraph). - Read the compiled specifications:
spec/compiled/SuperPRD.mdand allMiniPRD_*.mdfiles. - Read all files in
.agents/memory/and.agents/rules/.
- Read the deterministic state:
-
Explore the Current Codebase
- Use directory listing to get a high-level view of the project structure (
src/,tests/, etc.). - Use search and file reading to inspect key files and understand implementation details.
- Goal: Build a fresh mental model of the actual codebase state vs. what the Hypergraph currently documents.
- Use directory listing to get a high-level view of the project structure (
-
Synthesize Findings
- Compare your exploration findings with the current memory state.
- Identify discrepancies (e.g., deprecated dependencies still mentioned, new patterns not documented, renamed files).
-
Refresh the Memory Files
activeContext.md: Update with the current development focus, recent changes, and immediate next steps.systemPatterns.md: Update with new recurring patterns. Remove replaced ones. Document the actual architecture.productContext.md: Update if product goals have evolved or features have changed.
-
Sync Documentation
- If abstract patterns or rules are outdated, update
.agents/memory/systemPatterns.mdor the relevant.agents/rules/file. - CRITICAL: Do NOT manually edit
architecture.yml. If the Hypergraph is out of sync with reality, instruct the user to run/hyper-discoveror/hyper-auditto deterministically reconcile it.
- If abstract patterns or rules are outdated, update
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.
- 2mo ago First seen · 45 lines · 48 tokens per session scan A 0afe662ffc5a
refresh-memory is a skill published in the GitHub repository tjmustard/Hypergraph-Coding-Agent-Framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 556 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 2026-08-31.
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