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 phuonghx/aim-cli --skill project-memorygit 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/skills/phuonghx/aim-cli/project-memory)<a href="https://agentmods.dev/skills/phuonghx/aim-cli/project-memory"><img src="https://agentmods.dev/badge/skills/phuonghx/aim-cli/project-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/phuonghx/aim-cli/project-memory"><img src="https://agentmods.dev/badge/skills/phuonghx/aim-cli/project-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 | $0.00038 | $0.00455 |
| Opus 5.5 | $0.00015 | $0.00182 |
| Sonnet 5.5 | $0.00008 | $0.00091 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
project-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 1mo 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
Project Memory (aim-memory)
Memory is the cognitive backbone of AI-native development. Because LLMs are stateless by default, project context must be stored deterministically in the codebase.
1. Directory Structure
Memory is organized under the .ai-context/ directory:
.ai-context/config.json: The single source of truth for project metadata, stack, and commands..ai-context/skills/: Holds the active AIM skills..ai-context/docs/: Directory for Markdown documentation files.
2. Tasks & Progress (Task Mode)
During execution, use planning tools to log tasks:
- Maintain a structured task list in your brain directory (
task.md). - Mark tasks with
[ ](todo),[/](in-progress), and[x](completed). - Use Conventional Commits (
feat:,fix:,docs:,refactor:) when finalizing task items.
3. Documentation & Cross-Referencing
Keep documentation clean, modular, and cross-referenced:
- Task Mentions: Refer to tasks in files or commit messages using
@task-<id>. - Doc Mentions: Link to Markdown docs using
@doc/<path>. - Code Line Links: Reference specific lines using
@doc/<path>:12or ranges using@doc/<path>:10-25. - Anchors: Reference markdown sections using
@doc/<path>#section-slug.
4. Session memory policy
At the end of a session or task:
- Evaluate whether any new design decision, architecture pattern, user preference, or recurring error should be saved as persistent memory.
- Store project-specific rules in local docs or
.ai-context/config.json. - Store global user preferences in global files so they carry across sessions.
- Default to saving durable rules automatically without waiting for explicit user instructions.
- Never duplicate full documentation code blocks into memory; summarize and reference the file path instead.
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.
- 1mo ago First seen · 40 lines · 38 tokens per session scan A f2b83eeddc8e
project-memory is a skill published in the GitHub repository phuonghx/aim-cli (1 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 455 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.
Other skills, from other repositories
hindsight-architect
Expert memory architect. Understands your application, identifies where memory adds value, and produces an implementation plan with bank config, tag schema, and code.
hindsight-local
Store user preferences, learnings from tasks, and procedure outcomes. Use to remember what works and recall context before new tasks. (user).
create-agent
Create a new Hindsight-powered subagent with long-term memory. Use when the user wants a specialized agent that learns and remembers across sessions.
hindsight-docs
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
hindsight-memory
Long-term memory for the agent via Hindsight. Use to recall relevant past context before answering, retain durable facts as you learn them, and reflect over accumulated memory for the "why" behind a decision. Load whenever continuity across sessions matters — the user refers to earlier work, states a lasting…
bot-handoff
Keep a durable record of work passed between Bots in the shared Hindsight memory bank. Use when handing work to another Bot, when picking up work another Bot started, and when a finding would help other Bots, including Bots that are not part of the current conversation.