remember-md/remember/ask

Claude Code and agent skill by remember-md/remember

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Ask a natural-language question of your second brain. The AI reformulates as optimal search queries, calls the `mcp__remember__search_brain` tool, and synthesizes an answer with citations.

Install

npx vskill@latest install remember-md/remember/ask

SKILL.md

/remember:ask — Ask the Brain

Wraps the mcp__remember__search_brain MCP tool with: query reformulation, multi-call retry, citation-rich answer synthesis, and honest "not found" handling.

Prerequisite

The @remember-md/mcp server must be configured in the host's MCP config (added automatically by /remember:init since plugin v2.5.0). The tool mcp__remember__search_brain must be available in this session. If it isn't:

⚠️ The brain search MCP server isn't connected. Run `/remember:init` to
auto-configure, then restart Claude Code.

Don't proceed without the tool — there's no fallback in v1.


Step 1: Parse the user's question

The slash command is invoked as /remember:ask <question>. If the question is empty or only the slash command itself, ask the user what they want to know and stop.

Note the user's language (Romanian / English / mixed). Final answer will mirror the user's language unless content forces English (e.g., technical terms).

Step 2: Reformulate the query

Convert the natural-language question into a topical search phrase that matches how the brain is actually written. Apply these rules (also documented in the search_brain tool description — read it before this step):

  • 3–7 words, declarative noun-phrase
  • Strip stopwords + question words ("what", "how", "ce", "cum", "do I", "am I")
  • Keep nouns, concepts, proper names
  • Language match the content, not the question. Technical notes in this brain are usually English. Personal/strategic/relational notes are usually Romanian. If unsure, plan to try both languages (Step 3 retry).
Quick reformulation table
User saysReformulated query
"what do I think about postgres for small projects"postgres small projects preferences
"who works on dollie"dollie project people contributors
"ce decizii am luat în martie"decisions march 2026
"ce stiu despre cezar"cezar (proper name; let BM25 + wikilinks carry it)
"cum lucrez în paralel pe proiecte"multiple parallel projects orchestration
"what's my strategic direction for 2026"strategic direction 2026 priorities
"ce zice persona despre comunicare"SKIP — Persona is already in your session context

If the question is trivially answered by content already in the Persona block (Mission, Directives, recent Evidence Log), answer directly without calling the tool. Don't waste a tool call on Persona content.

Step 3: Call mcp__remember__search_brain

mcp__remember__search_brain({ query: "<reformulated phrase>", top_k: 8 })

Default top_k: 8. Use:

  • 5–7 for focused queries (one specific fact/decision)
  • 10–15 for broad surveys ("what do I know about X")
  • 20+ for "give me everything on this topic"

Step 4: Evaluate result quality and retry if weak

Strong = top result has score >= 0.025 AND its path/heading_path/text obviously matches the user's intent.

Weak = top result score < 0.020, OR results are off-topic, OR note says vector index is building (BM25-only mode).

If weak, retry once or twice with alternative phrasing:

  1. Try a different keyword set (synonyms, broader/narrower concepts)
  2. Try the other language (RO ↔ EN)
  3. For "decision" queries that miss, try the project name directly
  4. For person queries that miss, try the person's project as second hit

Cap at 3 total search_brain calls per /remember:ask invocation. Don't loop.

Step 5: Synthesize the answer

Write a natural-language answer in the user's language (Romanian if they asked in Romanian, English if they asked in English; mix when the content is mixed).

Structure:

  1. Direct answer in 1–2 sentences. Lead with the conclusion.
  2. Supporting evidence — bullets or table with [[wikilinks]] citing the exact paths from results[].path. Quote concise snippets when they carry weight.
  3. Caveats when relevant (data is stale, decision was for a specific project, contradiction noted, etc.)
  4. Closing if useful — pointer to the source-of-truth file with strongest score.

Wikilink format: [[Notes/foo.md]] or [[Notes/foo.md|short label]]. Use the exact path from the tool result so Obsidian can resolve it.

Quote text field directly when concise (1–3 sentences). For longer chunks, paraphrase + cite. Never paraphrase technical details (paths, IDs, dates, names) — quote those verbatim.

Step 6: Honest "not found" handling

If after up to 3 search calls the brain genuinely doesn't contain a relevant answer:

Brain-ul nu pare să aibă informații despre <topic>.
Cele mai apropiate hits au scor sub 0.02 și sunt off-topic
(top: [[<path>]] — <heading_path>).
💡 Want me to remember this? Reply: `remember this: <whatever the user wanted to capture>`

Never invent content from outside the brain. If the brain is silent, say so. Adjacent or off-topic results should not be presented as if they answer the question.

Step 7: Confirm format

Final answer should always include:

  • ✅ Direct answer (not just dump of results)
  • ✅ Wikilink citations using exact result paths
  • ✅ User's language (don't switch to English when they asked in Romanian)
  • ❌ No hallucinated content beyond what the tool returned
  • ❌ No raw JSON of tool output dumped at the user

Worked examples

Example A — entity lookup

User: /remember:ask cine este cezar

Reformulated: cezar

Tool call: mcp__remember__search_brain({ query: "cezar", top_k: 5 })

Answer (Romanian, since user asked in Romanian):

[[People/cezar.md|Cezar]] este [synthesize from result text]. Lucrează la [[Projects/X|X]]. Ultimul context relevant: [quote from result].
Surse: [[People/cezar.md]], [[Journal/2026-…|recent journal]].
Example B — decision recall

User: /remember:ask ce am decis despre netopia la 3dtoys

Reformulated: netopia 3dtoys exclusive payment provider

Tool call: above. If implementation plan ranks higher than decision note: Retry: decision netopia only 3dtoys

Answer:

Ai decis ca Netopia să fie singurul provider de plată pentru 3DToys ([[Notes/decision-netopia-only-3dtoys.md]]). Motivare: [quote].
Implementare în [[Projects/3dtoys/projects/3dtoys-site/NETOPIA_IMPLEMENTATION_PLAN.md]].
Example C — empty result

User: /remember:ask what do I think about react native mobile apps

Reformulated: react native mobile app preferences

Tool call: returns only 2 future-plan mentions (Remember GTM Phase 3), top score 0.0167.

Answer:

Brain-ul nu are o opinie capturată despre React Native mobile apps.
Singurele 2 mențiuni sunt planuri viitoare pentru un app mobil al Remember.md ([[Projects/remember/remember.md]] și [[Journal/2026-02-08.md]]) — nu o preferință personală.
💡 Want me to remember this? Reply: remember this: ...

Error handling

ScenarioBehavior
mcp__remember__search_brain not availableTell user to run /remember:init + restart
Tool returns note: "Vector index building"Use BM25 results, mention "(semantic indexing in progress, results may improve in a few minutes)"
Tool returns empty results arrayTreat as "not found" per Step 6
Tool throwsSurface the error message verbatim and suggest /remember:status
User asks something already in PersonaAnswer from Persona directly; skip the tool call

Anti-patterns

  • ❌ Don't dump raw JSON of search_brain output at the user. Synthesize.
  • ❌ Don't translate citations — wikilinks must use exact result paths.
  • ❌ Don't loop beyond 3 search calls per ask invocation.
  • ❌ Don't claim knowledge the tool didn't return. Brain-silence is honest output.
  • ❌ Don't translate user's language in the answer just because the brain content is the other language — quote in original, summarize in user's language.
  • ❌ Don't re-query for Persona content — it's already in your session context.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
58
Repository forks
6
7-day trend score
20

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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