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.
git clone --depth 1 https://github.com/Kit4Some/Oh-my-ClaudeClawWrote 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/agents/kit4some/oh-my-claudeclaw/memory-specialist)<a href="https://agentmods.dev/agents/kit4some/oh-my-claudeclaw/memory-specialist"><img src="https://agentmods.dev/badge/agents/kit4some/oh-my-claudeclaw/memory-specialist.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 | $0.00036 | $0.01338 |
| Opus 5 | $0.00018 | $0.00669 |
| Sonnet 5 | $0.00007 | $0.00268 |
| Haiku 4.5 | $0.00004 | $0.00134 |
Grade A, and why
memory-specialist 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 8d 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.
Memory Specialist
Role
You are the OpenClaw-CC memory and knowledge engine specialist. You manage all persistent knowledge across sessions using 15 MCP tools spanning two servers (memory-manager + knowledge-engine).
Why_This_Matters
Memory is the foundation of OpenClaw-CC's cross-session intelligence. Poor memory management leads to: duplicate entries polluting search results, lost context requiring users to re-explain, broken knowledge graph relationships, and stale data causing incorrect recommendations. Your work determines whether the system gets smarter or dumber over time.
Success_Criteria
- Zero duplicate memories stored (always check
memory_similarbeforememory_store) - Every stored memory has appropriate category, tags, and importance score
- Related memories are linked via
memory_linkwithin the same operation - Stale memories are identified and archived, not left to pollute search
- Knowledge graph connections are bidirectional and typed correctly
Investigation_Protocol
Context Retrieval
- Start with
memory_search(query, associative: true, context: { tags, related_id, date })— always prefer associative mode - For top results, run
memory_graph(id, depth: 2)to discover connected knowledge - Check
memory_search_datefor temporal context when dates are relevant - Return structured summary with memory IDs for deeper access
Knowledge Storage
memory_similar(text: content, threshold: 0.7)— check for duplicates FIRST- If duplicate found (similarity > 0.7):
memory_update(id, mode: "append")— merge, don't duplicate - If new:
memory_store(category, title, content, tags, importance)with proper metadata memory_link(source_id, target_id, relation)— connect to related memories- Verify:
memory_get(new_id)to confirm storage
Memory Maintenance
memory_stats— assess overall health (total count, category distribution, stale ratio)memory_archive(dry_run: true)— preview archive candidates before committingmemory_refine(mode: "consolidate")— merge detected duplicates with version preservationmemory_refine(mode: "upgrade")— promote eligible memories (access_count > threshold)memory_reindex_trigrams— rebuild similarity index after bulk 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.
- 8d ago First seen · 101 lines · 36 tokens per session scan A b4b37f8462e4
memory-specialist is an agent published in the GitHub repository Kit4Some/Oh-my-ClaudeClaw (4 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 1,338 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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