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 commands/rjmurillo/ai-agents/memory-exploregit clone --depth 1 https://github.com/rjmurillo/ai-agentsWhat 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 | $0.00024 | $0.00780 |
| Opus 5 | $0.00012 | $0.00390 |
| Sonnet 5 | $0.00005 | $0.00156 |
| Haiku 4.5 | $0.00002 | $0.00078 |
Grade A, and why
memory-explore 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Explore
Deprecated: Use the
exploring-knowledge-graphskill for deep exploration (Issue #2103 folded the former context-retrieval agent into it). See Memory Interface Decision Matrix.
Perform deep knowledge graph traversal using a lightweight subagent.
Query: $ARGUMENTS
Use the Task tool to launch a subagent:
Task({
subagent_type: "general-purpose",
model: "haiku",
description: "Explore Forgetful graph",
prompt: <see below>
})
Subagent Prompt
Use this prompt, substituting the user's query:
Explore the Forgetful knowledge graph for: "{user query}"
## Exploration Strategy
- Explore DEEPLY - follow links aggressively, expand entities, traverse relationships
- Be thorough - token cost is acceptable for comprehensive exploration
- Track visited IDs to prevent cycles
- But only SURFACE results relevant to the user's query in your final response
- Filter out tangential discoveries - the main agent only needs focused, relevant context
Execute these phases sequentially:
**Phase 1 - Semantic Entry:**
execute_forgetful_tool("query_memory", {
"query": "{user query}",
"query_context": "Deep exploration via /memory-explore command",
"k": 5,
"include_links": true,
"max_links_per_primary": 5
})
Collect all primary_memories and linked_memories.
**Phase 2 - Expand Memory Details:**
For each primary memory, call:
execute_forgetful_tool("get_memory", {"memory_id": <id>})
Extract: document_ids, code_artifact_ids, project_ids, linked_memory_ids
**Phase 3 - Entity Discovery:**
For discovered project_ids, call:
execute_forgetful_tool("list_entities", {"project_ids": [<ids>]})
**Phase 4 - Entity Relationships:**
For each relevant entity, call:
execute_forgetful_tool("get_entity_relationships", {
"entity_id": <id>,
"direction": "both"
})
**Phase 5 - Entity-Linked Memories:**
For each entity, call:
execute_forgetful_tool("get_entity_memories", {"entity_id": <id>})
Fetch any new memories not already visited.
---
**IMPORTANT: Filter and summarize before returning.**
You may have explored dozens of nodes - only include those RELEVANT to "{user query}".
Return a structured summary:
## Memories Found
**Primary (N):**
- [Title] (importance: X) - brief content snippet...
**Linked (N):**
- [Title] (importance: X) - connection type...
**Entity-linked (N):**
- [Title] - discovered via [Entity Name]...
## Entities Discovered
- [Name] (type) - X relationships, Y linked memories
## Documents & Artifacts
- [Title] (type/language) - if any found
## Graph Summary
- Total: X memories, Y entities, Z documents/artifacts
- Key themes: [identified clusters]
- Suggested follow-up: /memory-explore "[related query]"
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 · 115 lines · 24 tokens per session scan A 24c8ce50157b
memory-explore is a command published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed 2d ago), licensed MIT. It adds 24 tokens to every session and 780 once invoked, about $0.0001 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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pr
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cm
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cp
Stage, commit, and push the current branch following git governance rules.