Borrowing it
Nothing to install: this file belongs to raoulbia-ai/claude-recall. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/raoulbia-ai/claude-recall/main/.claude/skills/memory-management/SKILL.mdgit clone --depth 1 https://github.com/raoulbia-ai/claude-recallWrote 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/raoulbia-ai/claude-recall/memory-management)<a href="https://agentmods.dev/skills/raoulbia-ai/claude-recall/memory-management"><img src="https://agentmods.dev/badge/skills/raoulbia-ai/claude-recall/memory-management/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/raoulbia-ai/claude-recall/memory-management"><img src="https://agentmods.dev/badge/skills/raoulbia-ai/claude-recall/memory-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 38 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00061 | $0.02612 |
| Opus 5 | $0.00030 | $0.01306 |
| Sonnet 5 | $0.00012 | $0.00522 |
| Haiku 4.5 | $0.00006 | $0.00261 |
Grade A, and why
memory-management 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 12d 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Management
Persistent memory system that ensures Claude never repeats mistakes and always applies learned patterns across conversations.
4 Tools
mcp__claude-recall__load_rules- Load all active rules before starting work. No query needed.mcp__claude-recall__store_memory- Store a rule or learning. Immediately active in this conversation.mcp__claude-recall__search_memory- Search memories by keyword. Use to find specific memories before making decisions.mcp__claude-recall__delete_memory- Delete a specific memory by ID. Use search_memory first to find the ID.
When to Use
Loading (Recall)
- First action of every session — Call
load_rulesbefore ANY tool call, including Read/Glob/Grep. Rules must inform exploration, not just editing. - After context compression — If context was compressed or conversation is long, call
load_rulesagain. Earlier rules may have been lost. - Switching task areas — When moving from one domain to another (e.g., tests → database → CI), call
search_memorywith the new area as query. - Before modifying a file — Call
search_memorywith the file path or module name to check for file-specific conventions.
Storing (Capture)
- When user corrects your work - Call
store_memorywithmetadata.type: "correction" - When user mentions preferences - Call
store_memorywithmetadata.type: "preference" - After overcoming a challenge - Call
store_memorywithmetadata.type: "failure" - DevOps/workflow rules - Call
store_memorywithmetadata.type: "devops"
Key Directives
- ALWAYS load rules before acting — Call
load_rulesas your very first action in a session, before even reading files. Rules inform how you explore, not just how you edit. - ACT on loaded rules — After loading, state which rules apply to your current task before proceeding. If a rule conflicts with your plan, follow the rule. If none apply, say so. Loading without applying is the same as not loading.
- Cite applied rules inline — When a rule influences your work: (applied from memory: ). Place the citation next to the action it influenced, not at the end of unrelated text.
- User says "recall" / "remember" / "store this" → use Claude Recall — When the user says any of these keywords, ALWAYS use
mcp__claude-recall__store_memory. Do NOT write to the native memory directory (~/.claude/projects/*/memory/) for these requests. Claude Recall is the user's preferred memory system. - Ask before storing — Before calling
store_memory, tell the user what you plan to store and ask for confirmation - Capture corrections immediately — User fixes are highest priority (still ask first)
- Never store secrets — No API keys, passwords, tokens, or PII
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.
- 12d ago First seen · 240 lines · 61 tokens per session scan A 3069e3a2f081
memory-management is a skill published in the GitHub repository raoulbia-ai/claude-recall (23 stars, last pushed 23d ago), licensed MIT. It adds 61 tokens to every session and 2,612 once invoked, about $0.0003 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.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.