recall-context

Recall Context

Proactive memory retrieval that pulls prior context relevant to the work about to happen. Reduces "starting from scratch" errors and prevents the agent from re-deriving conclusions already captured in mnemo.

When to Use

• Session start: load any preferences, decisions, or open questions tied to the current cwd / project before the user types their first prompt.
• Before a significant decision: surface prior decisions in the same area (e.g. database choice, lint rules, deployment target) so the agent does not contradict an earlier conclusion.
• When the user names a topic: e.g. "let's work on the auth flow" - pull memories tagged or describing auth before proposing a plan.
• After a long context gap: if the conversation referenced earlier decisions but the agent does not have them in working memory, recall them on demand.

Steps

1. Resolve query terms from the trigger:

   • cwd: use the current working directory path + project name as the query (e.g. mnemo-mcp or /c/Users/.../wet-mcp).
   • recent: use the last 5-10 file paths the agent edited or read.
   • <topic>: use the topic verbatim (the user's words).
   • Default (no arg): combine cwd + last 3 file paths.

2. Search mnemo with context_type filtering when applicable:

   memory(action="search",
          query="<resolved query>",
          context_type=null,
          limit=10,
          include_archived=false)
   

   • For decisions only: pass context_type="decision".
   • For preferences only: pass context_type="preference".
   • Without filter, results span all six context types.

3. Synthesize results into a 2-3 sentence summary grouped by type:

   • decisions, preferences, facts, open tasks
   • Present to the user as: "From prior sessions: ..."
   • Include memory IDs for any item the user might want to update or delete later.

4. Skip silently if mnemo is offline (tool errors), returns 0 results, or only returns low-relevance matches (rerank_score < 0.3). Do not inject noise into the conversation.