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 commands/phuonghx/aim-cli/aim-extractgit clone --depth 1 https://github.com/phuonghx/aim-cliWrote 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/commands/phuonghx/aim-cli/aim-extract)<a href="https://agentmods.dev/commands/phuonghx/aim-cli/aim-extract"><img src="https://agentmods.dev/badge/commands/phuonghx/aim-cli/aim-extract.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 | $0.00015 | $0.00240 |
| Opus 5 | $0.00008 | $0.00120 |
| Sonnet 5 | $0.00003 | $0.00048 |
| Haiku 4.5 | $0.00002 | $0.00024 |
Grade A, and why
aim-extract 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 yesterday.
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
Extract Project Memory & Patterns
Analyze the current session, recent modifications, or code files, and extract reusable rules, schemas, decisions, or architectural patterns into AIM's persistent context.
Instructions:
- Examine recently modified files (e.g. using
git status -sor reviewing diffs) and chat history to identify reusable decisions, coding rules, patterns, schemas, or constraints. - For micro-rules, decisions, or conventions, add them to AIM memories using
aim memory add:- Project-specific rule:
aim memory add "Rule/Decision description" -c [decision|syntax|pattern] -l project --importance [1-10] - Global user preference:
aim memory add "Preference description" -c [decision|syntax|pattern] -l global
- Project-specific rule:
- For comprehensive guides, APIs, or architectural designs, create a doc file:
aim doc create "Title" -d "Summary description" -f [folder]
- Run
aim syncto compile the new context into active rules.
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.
- yesterday First seen · 17 lines · 15 tokens per session scan A c06c93d14c54
aim-extract is a command published in the GitHub repository phuonghx/aim-cli (1 stars, last pushed 2mo ago), licensed MIT. It adds 15 tokens to every session and 240 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 2026-09-03.
Other commands, from other repositories
avvarre:garden
Audit the workspace persistent memory folders (.avvarre/) to detect context drift, conventions mismatch, and stalled task lists.
memory-gc
Inspect or rotate hunt-memory JSONL files (audit.jsonl, patterns.jsonl, journal.jsonl). Caps file size and keeps N rotated backups so memory does not grow unbounded.
pickup
Pick up a previous hunt on a target — shows hunt history, untested endpoints, and memory-informed suggestions. Usage: /pickup target.com.
remember
Log current finding or successful pattern to hunt memory. Auto-fills from /validate output if available. Usage: /remember.
graph
Generate an interactive visual graph of your memories. Powered by graphify (github.com/safishamsi/graphify, MIT).
dejavu-memory
Lightweight memory primitives — record-version (v0.8.4) + backfill-gists (v0.8.6).