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 skills/sneg55/agent-starter/remembernpx skills add sneg55/agent-starter --skill remembergit clone --depth 1 https://github.com/sneg55/agent-starterWhat 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 | $0.00038 | $0.00809 |
| Opus 5 | $0.00019 | $0.00404 |
| Sonnet 5 | $0.00008 | $0.00162 |
| Haiku 4.5 | $0.00004 | $0.00081 |
Grade A, and why
remember 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 2d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Review
Goal
Review the user's memory landscape and produce a clear report of proposed changes, grouped by action type. Do NOT apply changes - present proposals for user approval.
Steps
1. Gather all memory layers
Read CLAUDE.md and CLAUDE.local.md from the project root (if they exist). Your auto-memory content is already in your system prompt - review it there. Note which team memory sections exist, if any.
Success criteria: You have the contents of all memory layers and can compare them.
2. Classify each auto-memory entry
For each substantive entry in auto-memory, determine the best destination:
| Destination | What belongs there | Examples |
|---|---|---|
| CLAUDE.md | Project conventions and instructions for Claude that all contributors should follow | "use bun not npm", "API routes use kebab-case", "test command is bun test", "prefer functional style" |
| CLAUDE.local.md | Personal instructions for Claude specific to this user, not applicable to other contributors | "I prefer concise responses", "always explain trade-offs", "don't auto-commit", "run tests before committing" |
| Team memory | Org-wide knowledge that applies across repositories (only if team memory is configured) | "deploy PRs go through #deploy-queue", "staging is at staging.internal", "platform team owns infra" |
| Stay in auto-memory | Working notes, temporary context, or entries that don't clearly fit elsewhere | Session-specific observations, uncertain patterns |
Important distinctions:
- CLAUDE.md and CLAUDE.local.md contain instructions for Claude, not user preferences for external tools (editor theme, IDE keybindings, etc. don't belong in either)
- Workflow practices (PR conventions, merge strategies, branch naming) are ambiguous - ask the user whether they're personal or team-wide
- When unsure, ask rather than guess
Success criteria: Each entry has a proposed destination or is flagged as ambiguous.
3. Identify cleanup opportunities
Scan across all layers for:
- Duplicates: Auto-memory entries already captured in CLAUDE.md or CLAUDE.local.md → propose removing from auto-memory
- Outdated: CLAUDE.md or CLAUDE.local.md entries contradicted by newer auto-memory entries → propose updating the older layer
- Conflicts: Contradictions between any two layers → propose resolution, noting which is more recent
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.
- 2d ago First seen · 68 lines · 38 tokens per session scan A 5514bc9c52a8
remember is a skill published in the GitHub repository sneg55/agent-starter (76 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 809 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 2026-08-30.
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