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 agentmods add skills/amanasmuei/amem/contextnpx skills add amanasmuei/amem --skill contextgit clone --depth 1 https://github.com/amanasmuei/amemWrote 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/amanasmuei/amem/context)<a href="https://agentmods.dev/skills/amanasmuei/amem/context"><img src="https://agentmods.dev/badge/skills/amanasmuei/amem/context.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.00279 |
| Opus 5 | $0.00018 | $0.00139 |
| Sonnet 5 | $0.00007 | $0.00056 |
| Haiku 4.5 | $0.00004 | $0.00028 |
Grade A, and why
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 3d 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.
What it actually says
Load Memory Context
Load all relevant memory context for a topic or the current task.
Instructions
-
Determine the topic from the user's request or the current conversation context.
-
Execute this sequence: a. Call
memory_injectwith the topic — surfaces corrections (MUST follow) and decisions (SHOULD follow) b. Callreminder_check— show any overdue or upcoming reminders c. Callmemory_tierwithaction: "list",tier: "core"— load always-on context d. If more context needed, callmemory_contextwith the topic for broader background -
Present the context naturally:
- Lead with corrections: "I remember these constraints..."
- Then decisions: "Previous decisions on this topic..."
- Then patterns/preferences if relevant
-
Apply corrections as absolute constraints — never violate them.
When to Use
- Start of any new task or topic
- When the user asks "what do you know about X?"
- When switching between different parts of the codebase
- Before writing code that might have constraints
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.
- 3d ago First seen · 33 lines · 37 tokens per session scan A 81ae19d63894
context is a skill published in the GitHub repository amanasmuei/amem (2 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 279 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 2026-08-31.
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