| name | recall |
| description | Smart graft search that picks the right tool (query → retrieve → explore) based on the question's shape, escalates when results are weak, and presents findings ranked by confidence with the originating evidence. Triggered by `/recall`, "do we have something about X", "have we seen this before", "ricordi se", "search the graph". Prefer this over a raw `graft query` whenever the user is exploring rather than confirming a known answer. |
recall — Smart, escalating search of the memory graph
graft exposes three search modes and they have different sweet spots:
| Mode | Best when |
|---|
query | The user is asking for the answer to a specific problem. Cache-style gating: STRONG / WEAK / MISS. |
retrieve | The user is exploring; they want top-K hybrid (lexical + semantic) ranked results. |
explore | The user names a topic + keywords; they want to walk the graph from there. |
This skill orchestrates them. Do not ask the user which mode — pick based on the question.
Argument shape
The user invokes you with a free-form question or topic.
| Pattern | Strategy |
|---|
| "how do I X" / specific problem statement | query → escalate to retrieve if MISS. |
| "what do we know about X" / open-ended topic | retrieve --top-k 10. |
| "X with Y" / topic with keyword anchors | explore "X" --keyword Y. |
| "find related to " | explore from that node's keywords (read via get). |
| "recent stuff about X" | retrieve and re-rank by node created_at if shown. |
If the user provides a --keyword style flag, respect it.
Cascade flow
┌─── STRONG → done; cite + use ───┐
graft query <Q> ──────────────┤ │
├─── WEAK → graft get <id> │── present
│ then continue │
└─── MISS → graft retrieve <Q>│
if 0 useful results: │
graft explore <Q>│
--keyword <inferred>│
Step 1 — query
graft query "<concise restatement of the user's question>"
Read result.hit:
- STRONG — high confidence near-exact match. Output: cite the node (
title, body), state explicitly "this is from a previous session", and stop. Do NOT re-derive the answer.
- WEAK — similar but not identical. Fetch the full body with
graft get <id_hex>, present it labeled as "WEAK match — review before using". Then proceed to Step 2 to find better candidates.
- MISS — go to Step 2.
Step 2 — retrieve
graft retrieve "<question>" --top-k 10
Read each result's title. Drop those with low score. If 1-3 are clearly relevant: present them ranked. If 0 useful: go to Step 3.
Step 3 — explore
Pick 1-3 keywords from the question. Use the same vocabulary the graph likely uses (run graft stats once if you've never seen this graph; the keyword distribution is implicit there). Then:
graft explore "<question>" --keyword <kw1> --keyword <kw2> --depth 3 --beam 4
If still nothing: tell the user explicitly "the graph has nothing on this", don't fabricate. Suggest they consider /memoryze-ing the eventual solution.
Cross-profile reach
If the user says "search across profiles" or you suspect the answer might be in a different profile:
for p in $(graft profile list | jq -r '.profiles[]'); do
echo "=== $p ==="
GRAFT_PROFILE=$p graft query "<question>"
done
Default behavior: stay in the current profile. Cross-profile is opt-in.
Output format to the user
Present in descending confidence:
STRONG (cache hit, profile=work):
→ <title>
<body trimmed if very long>
[id: <short_hex>]
WEAK (1 candidate, score 0.78):
~ <title> ← review before reusing
[id: <short_hex>]
Top-K (retrieve fallback, profile=work):
• <title> (score 0.62)
• <title> (score 0.55)
Avoid wall-of-JSON output. The CLI prints JSON; your job is to summarize it for the human.
Post-recall hooks
- If the result was used as the basis for a new solution that diverges meaningfully, suggest
/memoryze of the new variant.
- If there were multiple WEAK candidates that all looked redundant, suggest
/memory-audit — the graph may be accumulating duplicates.
- If
query returned MISS but retrieve had a great hit, that means the saved title doesn't match how the user phrases this. Suggest the user re-save with a better title, or do it yourself with their permission.
