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/ussdeveloper/memory-star/agents-mdgit clone --depth 1 https://github.com/ussdeveloper/memory-starWhat 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 | $0.01623 | $0.01623 |
| Opus 5 | $0.00812 | $0.00812 |
| Sonnet 5 | $0.00325 | $0.00325 |
| Haiku 4.5 | $0.00162 | $0.00162 |
Grade A, and why
memory-star AGENTS.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 today.
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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MemoryStar Agent Instructions
Place this file as .instructions.md or AGENTS.md in your project,
or add it to your agent's system prompt.
The agent will automatically use MemoryStar tools to manage
project knowledge.
MCP Tools - MemoryStar
You are connected to the MemoryStar MCP server - a local semantic memory database for this project. Use the tools below to save and search project information.
When to save (memory_save)
- When you discover a new pattern, convention, or structure in the code
- After analyzing architecture - save its description
- When you encounter non-standard dependencies or configurations
- After making a design decision - save as ADR (scope: "decisions")
- When you find a bug or workaround - scope: "bugs"
- CRITICAL: When your context usage approaches 85%, call
memory_context_check- the server will auto-save a summary
How to save
Use descriptive key and appropriate scope:
scope = "architecture" -> directory structure, layers, components
scope = "api" -> endpoints, controllers, GraphQL, REST
scope = "dependencies" -> libraries, versions, compatibility
scope = "patterns" -> code patterns, naming conventions
scope = "decisions" -> architectural decisions (ADR)
scope = "bugs" -> known bugs, workarounds
scope = "notes" -> general notes
Searching (memory_search)
Always search MemoryStar before starting work on a new task to check if notes already exist on the topic.
Use mode: "semantic" for conceptual queries (e.g. "how does auth work"),
and mode: "text" for specific keywords (e.g. "JWT token middleware").
Linking (memory_link)
Create relationships between notes to build a knowledge graph:
depends_on- component A depends on Bparent_of- parent modulereferences- loose associationimplements- interface/pattern implementation
Context Monitoring
Periodically check memory_context_check(context_usage_pct=..., project="your-project-name").
The server will assess whether a summary needs to be saved.
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.
- today First seen · 178 lines · 1,623 tokens per session scan A 3cf009426a7a
memory-star AGENTS.md is an instructions file published in the GitHub repository ussdeveloper/memory-star (0 stars, last pushed 2mo ago), licensed MIT. It adds 1,623 tokens to every session, about $0.0081 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
codemark GEMINI.md
Instructions for DanielCardonaRojas/codemark, covering development workflow and debugging with the tui logging system.
awesome-copilot-id AGENTS.md
Instructions for GulajavaMinistudio/awesome-copilot-id, covering communication, explanation and documentation, markdown formatting, user communication style and workflow & methodology.
hiveshare CLAUDE.md
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llm-safe-haven CLAUDE.md
Instructions for pleasedodisturb/llm-safe-haven, covering llm safe haven, what this is, project structure, tdd — non-negotiable (adopted 2026-08-17) and the contract.
kleosrules AGENTS.md
Instructions for kleosr/kleosrules, a project described as: Cursor harness pack: user rules, skills, Bash hooks, local HANDOFF memory. macOS, Linux, Windows (WSL).
coding-agent-safety-gate AGENTS.md
Instructions for ASER-ho/coding-agent-safety-gate, covering agents / 代理规则, 仓库类型 / repository type and ai 代理规则 / rules for ai coding agents.