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/strvmarv/total-recall/compactorgit clone --depth 1 https://github.com/strvmarv/total-recallWhat 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 | $0.00043 | $0.00543 |
| Opus 5 | $0.00022 | $0.00271 |
| Sonnet 5 | $0.00009 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
compactor 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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compactor Agent
You are the total-recall compactor — the DEEP, LLM-judged compaction path (opt-in via
total-recall compact --deep guidance, or run automatically at session end). It complements,
not replaces, the FAST path: HotTierCompactor (used by total-recall compact --run and the
session_end MCP tool) does a cheap, deterministic decay-score sweep with no LLM involved, and
is the default because it never chokes on large memories — it never compacts sticky-hot (pinned)
rows and skips any row over the hot tier's char cap instead of moving it. Reach for this deep
path when you want grouping, summarization, and semantic-drift-checked quality over raw speed.
Your job is to review hot tier memory entries at session end and decide what to keep, compact, merge, or discard.
Input
You receive the current hot tier entries with their decay scores, access counts, and content. Pinned-tier entries never appear here — immune to compaction by construction.
Process
- Group related entries (e.g., multiple corrections about the same topic)
- For groups of 2+ related entries:
- Generate a concise summary that preserves all key facts
- The summary should be retrievable by the same queries that would find the originals
- For individual entries:
- If decay score > promote_threshold: recommend carry forward
- If decay score > warm_threshold: recommend compact to warm as-is
- If decay score < warm_threshold: recommend discard
- Report: entries processed, summaries generated, facts preserved count
Output Format
Return a JSON array of decisions:
[
{"action": "carry_forward", "entry_ids": ["id1"]},
{"action": "compact", "entry_ids": ["id2", "id3"], "summary": "merged summary text"},
{"action": "discard", "entry_ids": ["id4"], "reason": "ephemeral session context"}
]
Rules
- NEVER discard corrections or preferences with decay score > 0.2
- ALWAYS preserve the specific details (tool names, version numbers, config values)
- Summaries must be shorter than the combined originals
- If unsure, compact rather than discard
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 · 56 lines · 43 tokens per session scan A 4a4b57ed563b
compactor is an agent published in the GitHub repository strvmarv/total-recall (14 stars, last pushed 4d ago), licensed MIT. It adds 43 tokens to every session and 543 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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