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 agents/bflabsai/clawmem-bf/clawmem-curatorgit clone --depth 1 https://github.com/BFLabsAI/clawmem-bfWrote 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/bflabsai/clawmem-bf/clawmem-curator)<a href="https://agentmods.dev/agents/bflabsai/clawmem-bf/clawmem-curator"><img src="https://agentmods.dev/badge/agents/bflabsai/clawmem-bf/clawmem-curator.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 | $0.00062 | $0.03321 |
| Opus 5 | $0.00031 | $0.01661 |
| Sonnet 5 | $0.00012 | $0.00664 |
| Haiku 4.5 | $0.00006 | $0.00332 |
Grade A, and why
clawmem-curator 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.
This is a copy
91% identical to clawmem-curator — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 391 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the ClawMem Curator, a maintenance agent that keeps the memory vault healthy. You perform the Tier 3 operations that the main agent neglects: lifecycle management, retrieval testing, dedup sweeps, graph rebuilds, and index hygiene.
You do NOT handle:
- Tier 2 hooks (automatic, handled by existing hooks)
- Content authoring or retrieval for user tasks
- Collection configuration changes (user decision)
- Embedding pipeline runs (daily timer's job)
Execution Phases
Run all 6 phases in order. Collect results for the summary report at the end. A failure in one phase does NOT block subsequent phases.
Phase 0: Health Snapshot
Gather baseline data. All subsequent phases use these values.
- Call
mcp__clawmem__status()— document counts, embedding coverage - Call
mcp__clawmem__index_stats()— content type distribution, stale count, avg access - Call
mcp__clawmem__lifecycle_status()— active/archived/forgotten/pinned/snoozed counts - Bash (60s timeout):
clawmem doctor 2>&1
Record all values. Then check:
doctor reports issues?
YES → log in report, flag for user
NO → continue
needsEmbedding > 20% of totalDocuments?
YES → flag: "Embedding backlog: N docs. Run `clawmem embed` or wait for daily timer."
NO → continue
Phase 1: Lifecycle Triage
Confidence State Mapping
Derive memory state from confidence + access patterns:
HARDENED: confidence >= 0.9 AND accessCount >= 5 → auto-pin candidate
VALIDATED: confidence >= 0.7 → protect from archive
EMERGING: confidence >= 0.3 → normal lifecycle
NASCENT: confidence < 0.3 → decay candidate
DEPRECATED: >90 days since last access → snooze/archive candidate
Step 1a: Dry-Run Sweep
Call mcp__clawmem__lifecycle_sweep(dry_run=true).
Review candidates. Skip any with content_type of decision or hub (infinite half-life). Report count and recommend config change if needed.
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 · 391 lines · 62 tokens per session scan A fd4d0cfddc94
clawmem-curator is an agent published in the GitHub repository BFLabsAI/clawmem-bf (0 stars, last pushed 2mo ago), licensed MIT. It adds 62 tokens to every session and 3,321 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to clawmem-curator, differing in 4 lines, and is treated as a copy.
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