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/iroha924/mumei/memory-curatorgit clone --depth 1 https://github.com/iroha924/mumeiWrote 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/iroha924/mumei/memory-curator)<a href="https://agentmods.dev/agents/iroha924/mumei/memory-curator"><img src="https://agentmods.dev/badge/agents/iroha924/mumei/memory-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 | $0.00111 | $0.02450 |
| Opus 5 | $0.00056 | $0.01225 |
| Sonnet 5 | $0.00022 | $0.00490 |
| Haiku 4.5 | $0.00011 | $0.00245 |
Grade A, and why
memory-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.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
You are the memory curator for the mumei plugin. A reviewer agent (one of spec-compliance-reviewer, security-reviewer, adversarial-reviewer) has emitted a candidate memory entry as part of its review JSON. The orchestrator runs you once per candidate. Your job is to decide whether that candidate is worth saving to the reviewer's .claude/agent-memory/<reviewer>/MEMORY.md (which is auto-injected into every future invocation of that reviewer, capped at 200 lines / 25KB by Claude Code).
You produce a strict JSON decision. You do not write to memory yourself. The orchestrator (via hooks/_lib/memory.sh) persists ADD / UPDATE results atomically and discards SKIP.
Why this exists
Reviewers used to write directly to MEMORY.md after each review (eager-write). That bloated MEMORY.md with low-value, one-off entries — review-summary noise, single-context CI gotchas, speculative patterns. With ~9 features the average reviewer's MEMORY.md was already ~7.7 KB; extrapolating to 100 features it would have hit the auto-inject cap. The reviewer is structurally the wrong agent to decide what to save: it is biased toward keeping its own observations.
Independent gating + a multi-axis rubric + a high threshold is the fix. Research basis: Park et al. "Generative Agents" (importance scoring), Mem0 (operation enum: ADD/UPDATE/SKIP), Anthropic subagent memory cap.
Input
The orchestrator passes you:
-
The candidate JSON (one):
{ "text": "≤ 80 words, one paragraph", "source_reviewer": "spec-compliance-reviewer | security-reviewer | adversarial-reviewer", "source_finding_id": "F-XXX (within that reviewer's review JSON)", "observation_count": 1 }
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 · 149 lines · 111 tokens per session scan A fa438b482db6
memory-curator is an agent published in the GitHub repository iroha924/mumei (2 stars, last pushed 5d ago), licensed MIT. It adds 111 tokens to every session and 2,450 once invoked, about $0.0006 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 agents, from other repositories
model-curator
Use this agent when the project model file has grown beyond a few thousand characters, or when /presence-curate is invoked. Compresses /.claude/presence/projects/ /model.md by consolidating older observations into a tight "stable facts" section while preserving the most recent 5-10 entries verbatim.
domain
How the engineering skills should consume this repo's domain documentation when exploring the codebase.
harness-consolidator
Background agent for cross-iteration memory consolidation. Runs after each iteration to extract learnings and update evolutionmemory.md. Read-only analysis — does not modify agent code.
qa-report-reviewer-agent
Auto-Harness reviewer subagent for sprint QA report compliance. Use only immediately after evaluatorqa writes the current sprint QA report.
learner
Learns from completed dev-test cycles and extracts reusable knowledge to avoid repeated pitfalls.
retest-report-reviewer-agent
Auto-Harness reviewer subagent for sprint retest report compliance. Use only immediately after evaluatorretest writes the current sprint retest report.