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 instructions/ozgurkarahan/ai-agent-memory/project-statusgit clone --depth 1 https://github.com/ozgurkarahan/ai-agent-memoryWrote 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/instructions/ozgurkarahan/ai-agent-memory/project-status)<a href="https://agentmods.dev/instructions/ozgurkarahan/ai-agent-memory/project-status"><img src="https://agentmods.dev/badge/instructions/ozgurkarahan/ai-agent-memory/project-status.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 5.1 | $0.01133 | $0.01133 |
| Opus 5 | $0.00566 | $0.00566 |
| Sonnet 5 | $0.00227 | $0.00227 |
| Haiku 4.5 | $0.00113 | $0.00113 |
Grade A, and why
ai-agent-memory project-status.instructions.md 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 5d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Status
When the user says "project status", "status briefing", or invokes /project-status from inside any project directory (NOT memory itself), produce a complete situational-awareness briefing so the user can get up to speed on that project in 30 seconds.
This skill is for any child project. When invoked from the memory system itself, refuse and direct the user to the wiki because the wiki is its status.
Coexists with the per-project
/statuscommand that ships in every scaffolded project under.claude/commands/status.md. The per-project version is Claude-Code-specific. THIS memory skill is the agent-agnostic version (works under GitHub Copilot CLI, Claude Code, or any tool that loads.github/instructions/). When both are available, prefer the per-project one if you are inside Claude Code (richer integration), otherwise use this skill.
Instructions
Gather information from ALL the sources below, then produce a single structured briefing. Use parallel tool calls to speed up the research.
Resolve the memory root
- If the current project contains
schema.mdormemory/schema.md, it is the memory system or its installer; refuse as described above. - Otherwise follow the memory-wiki path declared in the child project's
AGENT.md. - If no memory root resolves, continue the codebase briefing but mark the wiki page as unavailable instead of guessing a personal path.
1. Codebase analysis
- Tech stack: languages, frameworks, key dependencies (check
package.json,requirements.txt,pyproject.toml,*.csproj,Cargo.toml,go.mod,pom.xml, etc.) - Folder structure: high-level tree (max 2 levels deep), explain what each top-level folder contains
- Key files: entry points, config files, main modules
- Architecture patterns: monolith/microservices, API style (REST/GraphQL/gRPC), state management, key abstractions
- Size: approximate number of source files and lines of code
2. Project history — what we've done
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.
- 5d ago First seen · 101 lines · 1,133 tokens per session scan A 8d77f482d06c
ai-agent-memory project-status.instructions.md is an instructions file published in the GitHub repository ozgurkarahan/ai-agent-memory (8 stars, last pushed 1mo ago), licensed MIT. It adds 1,133 tokens to every session, about $0.0057 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.
Other instructions, from other repositories
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Claude Code instructions for aeonfun/aeon, covering aeon, how aeon works, strategy, voice and soul file hierarchy (read in this order).
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Claude Code instructions for ashlesh-t/cognirepo, covering claude.md, key rules, session start sequence (run in this order), behavioral confirmation rule and personas (cognirepo-402, cognirepo-403).
wayland-core copilot-instructions.md
Copilot instructions for FerroxLabs/wayland-core, covering ijfw rules, output discipline, memory routing, context discipline and cross-audit.
mcp-structured-memory CLAUDE.md
Claude Code instructions for nmeierpolys/mcp-structured-memory, a project described as: Structured Memory MCP Server.
inkwell-memory CLAUDE.md
Instructions for veronchenko/inkwell-memory, covering claude.md — inkwellmemory, layout, multi-tenant mode (inkwellmultitenant=1), conventions and testing.
memory-mcp-1file AGENTS.md
Instructions for pomazanbohdan/memory-mcp-1file, covering ⛔ l0 invariants (never violate under any circumstance), detection heuristic, 🔀 phase transition routing (⛔ blocking), gate-0: phase identification & loading and 🧾 proof-of-load requirement (critical).