hmem-search

name	hmem-search
description	Search hmem when the user references something without an ID — past conversations ('letzte Woche', 'remember when'), unknown proper names, definite articles assuming shared context ('the bug we had', 'das Schema von gestern'), or asks whether a schema/rule/decision is documented. Search first, ask second. Skip for explicit ID lookups like 'read P0048'.

hmem Search

When the user references past context without pinning it to an ID, or when looking up definitions, schemas, or decisions stored in hmem — convert the intent into a targeted read_memory query.

Workflow

1. Extract from the prompt:

   • Keywords — distinctive nouns, project names, error fragments, schema names. Skip filler like "wir", "neulich", "besprochen", "Schema für".
   • Time hint — map to after/before range using the current date as anchor. "gestern" → narrow (−1 to 0d), "letzte Woche" → medium (−10 to −3d), "neulich"/"vor kurzem" → generous (−21d). No time hint → skip the range.

2. First search:

   read_memory({ search: "<keywords>", after: "<ISO>", before: "<ISO>" })
   

   Keywords as a single space-separated string. Use ISO dates (2026-04-11), not relative forms.

3. If results are empty or off-topic — work through this sequence immediately, without waiting:

   a) Drop time filter, keep keywords Time hints from humans are fuzzy; the memory may sit just outside the window.

   b) Try term variations — systematically, not just once The stored entry may use a different phrasing than what the user said. Try all that apply:

   • German ↔ English: "Schema" → "schema", "Entscheidung" → "decision", "Fehler" → "error"
   • Abbreviations or expansions: "H-Schema" → "H-Entry Schema", "O-Eintrag" → "O-entry"
   • Compound splits: "Standardschema" → "Standard Schema", "Checkpoint-Strategie" → "checkpoint strategy"
   • Synonyms: "Kollision" → "conflict", "Struktur" → "structure", "Vorlage" → "template"
   • Broader category: "H-Standardschema" → "H-entry", "entry schema", "Human schema"
   • Related prefix: if the topic is about a specific entry type (H, P, E, I…), search that prefix directly via read_memory({ prefix: "R", search: "H" })

   Don't try one variation and stop. Run 2–3 variations before concluding nothing was found.

   c) Switch store Default is personal. If the topic is work-related and personal turned up nothing, try store: "company".

   d) Broaden with find_related If you found something related but not quite right, use find_related({ id: "<hit-ID>" }) to surface linked entries.

   Only report "nothing found" after all of these have failed.

4. Present the hits:

   • Top 3–5 most relevant: ID · date · one-line summary.
   • If the question implies drilling into one entry, offer read_memory({ id: "..." }) rather than dumping everything.

Why term variation matters

hmem entries are titled by whoever created them, not by a controlled vocabulary. "H-Standardschema" might be stored as "H-Entry Schema: Standard-Struktur für Human-Context-Einträge" (R0025). The search engine does substring/FTS matching, but only within what's actually stored. If the first search misses, the entry almost certainly exists under a different phrasing — not in a different location.

The failure mode to avoid: searching once, getting no results, and concluding the information doesn't exist. A null result is a signal to try harder, not a final answer.

The "assumed shared knowledge" trigger

The user often speaks as if you already know things you don't — because from their side, the conversation is continuous across sessions. Watch for:

• Definite articles without prior mention: "der Bug mit dem Sync", "das Problem von neulich", "die Entscheidung zum Schema" — the der/das/die implies you should know which one.
• Proper names dropped cold: a project, person, feature, or error name you haven't seen this session.
• Casual callbacks: "wie besprochen", "wie gesagt", "du weißt schon", "as we agreed".
• Assumed status: "wo stehen wir mit X?", "ist Y schon fertig?"
• Schema/rule lookups: "gibt es ein Standard für X?", "was ist das Schema für Y?", "was haben wir zu Z beschlossen?"

When this pattern shows up: search first, answer second.

Don't

• Don't pre-parse time into a fixed dictionary ("neulich" → 14d). Context shifts the right window.
• Don't silently search only personal when the context is clearly work-related.
• Don't return raw read_memory output to the user. Summarize what was found.
• Don't trigger when the user cites a specific ID — they already know where to look.
• Don't stop after a single null result. Work through the variation sequence before giving up.

Related tools

• search_memory — dedicated FTS5 endpoint; read_memory({ search }) covers the same ground with structured output.
• find_related(id) — after locating a hit, surface linked entries.
• read_memory({ time_around: "<ID>" }) — once you have an anchor, find entries created around the same time.
• read_memory({ prefix: "R" }) — scan all Rules when looking for documented standards or constraints.