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 skills/thinkfleetai/memmesh/forgetnpx skills add ThinkfleetAI/memmesh --skill forgetgit clone --depth 1 https://github.com/ThinkfleetAI/memmeshWhat 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 | $0.00073 | $0.00416 |
| Opus 5 | $0.00036 | $0.00208 |
| Sonnet 5 | $0.00015 | $0.00083 |
| Haiku 4.5 | $0.00007 | $0.00042 |
Grade A, and why
forget 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.
What it actually says
forget
Remove or correct what's in memory. Always confirm before deleting.
1. Find it
{ "name": "memory_search", "arguments": { "query": "<what to forget>", "projectId": "<repo>", "limit": 10 } }
Show the matches (id + content) and ask which to remove.
2. Delete
{ "name": "memory_delete", "arguments": { "id": "<id>" } } // soft: status→rejected, sync-safe
{ "name": "memory_delete", "arguments": { "id": "<id>", "hard": true } } // physical: GDPR / cleanup only
Default to soft delete — it stops surfacing in search and propagates the
rejection to peer stores over sync. Use hard: true only for right-to-forget or
operator cleanup.
Correction vs deletion
If the fact changed (not "was wrong to store"), don't delete — record a
correction so provenance survives: memory_observe the new statement, then
memory_supersede the stale id byId the new one. The engine also supersedes
automatically when you observe a contradiction, so plain memory_observe is
often enough.
Undo a just-added memory
If the user says "undo that" right after a save, search for the most recent item
in scope (memory_list), confirm it's the one, and memory_delete it.
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 · 46 lines · 73 tokens per session scan A 3759e01e86f0
forget is a skill published in the GitHub repository ThinkfleetAI/memmesh (440 stars, last pushed 7d ago), licensed Apache-2.0. It adds 73 tokens to every session and 416 once invoked, about $0.0004 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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