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/verygoodplugins/claude-pluginsWrote 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/commands/verygoodplugins/claude-plugins/memory-recall)<a href="https://agentmods.dev/commands/verygoodplugins/claude-plugins/memory-recall"><img src="https://agentmods.dev/badge/commands/verygoodplugins/claude-plugins/memory-recall/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/verygoodplugins/claude-plugins/memory-recall"><img src="https://agentmods.dev/badge/commands/verygoodplugins/claude-plugins/memory-recall.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00009 | $0.00268 |
| Opus 5.5 | $0.00004 | $0.00107 |
| Sonnet 5.5 | $0.00002 | $0.00054 |
| Haiku 4.5 | $0.00001 | $0.00027 |
Grade A, and why
memory-recall 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 1mo 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
Memory Recall
Perform context-aware memory search:
-
Analyze Context:
- Current working directory (extract project name)
- Recently opened files
- User's query or intent
-
Execute Recall:
Use
mcp__memory__recall_memorywith appropriate strategy:Project Context (default):
mcp__memory__recall_memory({ query: "[user query or project context]", tags: ["project-name"], limit: 10 })Recent Work:
mcp__memory__recall_memory({ tags: ["project-name"], time_query: "last 7 days", limit: 5 })Debug Similar Errors:
mcp__memory__recall_memory({ query: "[error message keywords]", tags: ["bug-fix"], limit: 5 }) -
Present Results: Show memories with:
- Content summary
- Creation date
- Importance score
- Actionable insights
Present the information naturally, not as a database query result.
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.
- 1mo ago First seen · 52 lines · 9 tokens per session scan A 8e068d5635ff
memory-recall is a command published in the GitHub repository verygoodplugins/claude-plugins (2 stars, last pushed 8mo ago), licensed MIT. It adds 9 tokens to every session and 268 once invoked, about $0.0000 per session on Opus 5.5. 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 commands, from other repositories
instinct-import
Import instincts from external sources.
learn
Extract patterns and learnings from current session.
context-save
Save project context, decisions, and progress for a later session.
recall-save
Generate / overwrite .recall/context.md with Recall's local offline summarizer.
export-closedloop-learnings
Exports pending ClosedLoop learnings to global location with deduplication.
cleanup
Sweep /.claude disk hygiene to stated retentions, clean up stale plans from repos, audit plugin health, and compact agent memory files.