project-memory

A project-memory system that stores project details, tasks, documentation, skills, and cross-references in an .ai-context directory. It gives an agent a consistent way to retain project information in the codebase.

In plain words
What is it for?
Use it to track tasks, maintain project documentation, reference files and code lines, and record structured project metadata.
Why use it?
It reduces repeated setup and lost context by keeping project instructions, progress, and document links in durable files.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/phuonghx/aim-cli/project-memory
Any agent
npx skills add phuonghx/aim-cli --skill project-memory
Clone the repo
git clone --depth 1 https://github.com/phuonghx/aim-cli

Made for: Claude Code, Codex.

Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 455 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00038 $0.00455
Opus 5 $0.00019 $0.00228
Sonnet 5 $0.00008 $0.00091
Haiku 4.5 $0.00004 $0.00046

Measured yesterday against content hash f2b83eeddc8e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 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.

aim/skills/project-memory/SKILL.md · 40 lines

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>:12 or 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.
Changes

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.

  1. yesterday First seen · 40 lines · 38 tokens per session scan A f2b83eeddc8e

Subscribe to this mod's changes

project-memory is a skill published in the GitHub repository phuonghx/aim-cli (1 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 455 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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