Skill v1.0.0

version: "1.0.0" name: rekal-save description: > End-of-session memory capture with deduplication. Extracts durable knowledge, checks for duplicates, stores or supersedes as appropriate. Use whenever a session wraps up, a task finishes, or the user says goodbye/thanks/done. Also use when significant preferences, decisions, or discoveries emerge mid-session. Make sure to trigger this skill proactively — err on the side of capturing. allowed-tools: mcp__rekal__memory_search mcp__rekal__memory_store mcp__rekal__memory_supersede mcp__rekal__memory_conflicts mcp__rekal__memory_set_project

Save durable knowledge from this session into rekal. Goal: user never repeats themselves across sessions.

Step 1: Extract candidates

Review the conversation. Per item, apply this filter:

Would a fresh agent in a new session benefit from knowing this?
├── YES → candidate
└── NO  → skip

Candidate types:

Skip — do not store:

• Transient state: "currently editing main.py", "tests passing now"
• Trivially re-discoverable: "function foo is on line 42", "file has 200 lines"
• Too vague: "user likes clean code", "project uses Python"
• Session mechanics: "user asked me to fix a bug", "we discussed testing"
• Secrets, API keys, passwords, tokens — never

If zero candidates survive, stop here. Do not force-store.

Step 2: Set project scope

Single-project session?
├── YES → memory_set_project(project="<name>")
│         All subsequent stores auto-scope to this project.
└── NO  → Skip. Set project= per memory in step 4.

Step 3: Deduplicate each candidate

For EVERY candidate, before storing:

memory_search(query="<candidate topic in natural language>", limit=5)

Read results. Apply:

Search returned results?
├── NO match at all
│   └── Proceed to step 4 (store new)
│
├── Same topic, same info (duplicate)
│   └── SKIP. Do not store.
│
├── Same topic, new/updated info
│   └── memory_supersede(old_id="<matched memory id>", new_content="<updated content>")
│
└── Same topic, contradictory info
    └── memory_supersede(old_id="<matched memory id>", new_content="<corrected content>")
        Include what changed and why in the content.

Critical rule: Two memories about the same topic must never coexist. Newer supersedes older. "User's preferred formatter" appears exactly once in the database.

Step 4: Store surviving candidates

Per candidate that passed dedup with no match:

memory_store(
    content="<self-contained content — what AND why>",
    memory_type="<one of: fact, preference, procedure, context, episode>",
    tags=["<tag1>", "<tag2>"],    # 2-4 specific tags. Not "code", "project", "general".
    project="<name>",             # Omit if memory_set_project was called, or if global.
)

Pick memory_type

Content must be self-contained

A fresh agent with zero conversation context reads this content. It must make complete sense alone.

Good: "User prefers Ruff over Black for formatting because it's faster
       and handles import sorting in a single tool"
Bad:  "User prefers Ruff"               — missing the why
Bad:  "As discussed, switch to Ruff"     — references conversation
Bad:  "The formatter preference"         — meaningless alone

Tags must be specific

Good: ["ruff", "formatting", "linting"]
Bad:  ["code", "tools", "project"]

Step 5: Conflict check + summary

memory_conflicts(project="<project if scoped>")

If new conflicts appear:

"Noticed conflict: [X] vs [Y]. Want me to resolve it?"

Summarize what was saved:

"Saved 3 memories: Ruff preference, deploy procedure, auth architecture. Superseded 1 outdated API endpoint memory."

If nothing was saved (all skipped as duplicates), say so:

"Reviewed session — no new knowledge to capture. Existing memories already cover it."

Boundaries

• This skill stores memories only. No reorganization, no cleanup — that's /rekal-hygiene.
• No conversation creation — captures knowledge FROM conversations, not about them.
• Never stores secrets, API keys, passwords, tokens.
• Ask user before storing sensitive or personal content (health, finance, relationships).