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/aliasjeff/aclix/memory_managernpx skills add AliasJeff/ACLIx --skill memory_managergit clone --depth 1 https://github.com/AliasJeff/ACLIxWhat 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 | $0.00018 | $0.00720 |
| Opus 5 | $0.00009 | $0.00360 |
| Sonnet 5 | $0.00004 | $0.00144 |
| Haiku 4.5 | $0.00002 | $0.00072 |
Grade A, and why
memory_manager 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 2d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Provide a reliable, repeatable procedure for an agent to inspect and update its Hierarchical Memory System:
- Long-Term Memory (LTM): permanent user/project instructions and facts
- Compressed Memory (CM): rolling historical summary inside the session
- Short-Term Memory (STM): recent uncompressed messages inside the session
Standard Operating Procedure
Key facts (read first)
- LTM is already injected into your System Prompt as
<long_term_memory>...</long_term_memory>. - Treat
<long_term_memory>as permanent instructions and facts. You MUST prioritize and adhere to it over ephemeral conversation text. - If LTM exceeds length thresholds, it is automatically chunked and ONLY the Top 3 BM25 retrieved fragments relevant to your current task are injected.
1) Inspect current STM/CM state (capacity/volume)
Use this when you need to answer questions like:
- “How many messages are in STM right now?”
- “Is Compressed Memory (historical summary) present?”
- “Has rolling compression already happened?”
Procedure
-
Read the injected anchor at the very top of the skill payload returned by
read_skill. Extract the absolute path from:[Skill Directory: <absolute_path>]- Call it
INJECTED_SKILL_DIR(the directory that contains this skill’sSKILL.md).
-
Invoke the
pythontool with:scriptPath:INJECTED_SKILL_DIR+/scripts/inspect.pyargs: one argument, the targetcwd(string)- Do not use the shell for this inspection.
-
Interpret the output:
- The script prints a single JSON object, including:
cwdmessageCountcompressedMemoryPresent(CM)shortTermMessageCount(STM)
- The script prints a single JSON object, including:
2) Update / remember new Long-Term Memory (CRITICAL)
CRITICAL RULE: To UPDATE or REMEMBER new long-term information, you MUST edit the LTM markdown files directly using file_edit or file_write.
- Global (user-level) LTM:
~/.aclix/ACLI.md- Use for: stable user preferences, writing style, tooling preferences, personal constraints, recurring workflows.
- Project (cwd-level) LTM:
./ACLI.md- Use for: repo-specific rules, architecture constraints, domain facts, deployment instructions, team conventions.
What ships with it
1 file 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.
- 2d ago First seen · 75 lines · 18 tokens per session scan A b8278802c273
memory_manager is a skill published in the GitHub repository AliasJeff/ACLIx (23 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 720 once invoked, about $0.0001 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 2026-08-30.
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