CtrlK
BlogDocsLog inGet started
Tessl Logo

memory-search

Query the raw trajectory SQLite database directly when the built-in memory and history tools are insufficient. Use when you need structured analysis across sessions: finding repeated errors, grouping tool calls by pattern, verifying what was actually executed, or locating specific past commands/decisions that text search cannot surface. Provides the database schema, ready-to-use SQL query templates, and per-goal strategies.

70

Quality

85%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Memory Search: SQLite Trajectory Database

Direct SQL access to mimocode's trajectory database for structured analysis that the memory (BM25 over curated markdown) and history (FTS over raw messages) tools cannot perform — aggregation, filtering by tool/status/time, cross-session pattern detection, and execution chain inspection.

When to use

  • You need to aggregate or count across sessions (e.g. "which tool fails most often?", "how many sessions touched file X?").
  • You need to filter by structure — tool name, status, agent_id, time range — not just text content.
  • You need to view a complete execution chain for a session (every tool call in order).
  • You need to verify a memory claim against what actually happened (the DB is the source of truth).
  • The memory and history tools returned nothing useful despite multiple query attempts.

Locating the database

# Typically at this path. MIMOCODE_DB env var overrides if set.
sqlite3 -readonly ~/.local/share/mimocode/mimocode.db ".tables"

Always use -readonly or only SELECT queries — never modify the database.

Schema

TablePurposeKey columns
sessionSession metadataid, project_id, title, time_created, parent_id
messageUser/assistant turnsid, session_id, agent_id, time_created, data (JSON: $.role)
partMessage parts (text, tool calls, steps)id, message_id, session_id, time_created, data (JSON)
taskTask treeid, session_id, summary, status
task_eventTask state transitionsid, session_id, task_id, at, kind, summary
actor_registrySubagent/peer historysession_id, actor_id, agent, mode, status, description

Part types in part.data

  • {"type":"text","text":"..."} — agent text output
  • {"type":"tool","tool":"<name>","callID":"...","state":{"status":"completed","input":{...},"output":"..."}} — completed tool call
  • {"type":"tool","tool":"<name>","callID":"...","state":{"status":"error","input":{...},"error":"..."}} — failed tool call (no output field; error message in $.state.error)
  • {"type":"step-start"} / {"type":"step-finish","tokens":...} — step boundaries
  • {"type":"compaction","auto":true/false} — compaction boundary
  • {"type":"checkpoint",...} — checkpoint/rebuild boundary

Key conventions

  • agent_id = 'main' = main agent; other values = subagent (e.g. "explore-1", "general-1").
  • $.state.output only exists when $.state.status = "completed". Failures store the message in $.state.error.
  • time_created is Unix milliseconds.

Query templates

List recent sessions for this project:

SELECT id, title, time_created,
       datetime(time_created/1000, 'unixepoch', 'localtime') as created
FROM session
WHERE project_id = '<PROJECT_ID>'
  AND parent_id IS NULL
ORDER BY time_created DESC
LIMIT 20;

Find user messages containing a keyword:

SELECT m.session_id, m.id,
       substr(json_extract(p.data, '$.text'), 1, 200) as preview
FROM message m
JOIN part p ON p.message_id = m.id AND p.session_id = m.session_id
WHERE json_extract(m.data, '$.role') = 'user'
  AND json_extract(p.data, '$.type') = 'text'
  AND json_extract(p.data, '$.text') LIKE '%keyword%'
ORDER BY m.time_created DESC
LIMIT 10;

Find tool calls by tool name:

SELECT m.session_id, m.id, m.agent_id,
       json_extract(p.data, '$.tool') as tool,
       json_extract(p.data, '$.state.status') as status,
       substr(COALESCE(json_extract(p.data, '$.state.output'), json_extract(p.data, '$.state.error')), 1, 300) as result_preview
FROM message m
JOIN part p ON p.message_id = m.id AND p.session_id = m.session_id
WHERE json_extract(m.data, '$.role') = 'assistant'
  AND json_extract(p.data, '$.type') = 'tool'
  AND json_extract(p.data, '$.tool') = '<TOOL_NAME>'
  AND m.session_id = '<SESSION_ID>'
ORDER BY m.time_created DESC
LIMIT 20;

View a session's full execution chain:

SELECT m.id, m.agent_id,
       json_extract(p.data, '$.type') as part_type,
       json_extract(p.data, '$.tool') as tool,
       substr(p.data, 1, 800) as preview
FROM message m
JOIN part p ON p.message_id = m.id AND p.session_id = m.session_id
WHERE m.session_id = '<SESSION_ID>'
  AND json_extract(m.data, '$.role') = 'assistant'
ORDER BY m.time_created, p.time_created;

Find repeated stdout errors (completed bash calls, last 7 days):

SELECT substr(json_extract(p.data, '$.state.output'), 1, 200) as error_output,
       COUNT(*) as occurrences,
       GROUP_CONCAT(DISTINCT m.session_id) as sessions
FROM part p
JOIN message m ON m.id = p.message_id AND m.session_id = p.session_id
WHERE json_extract(p.data, '$.type') = 'tool'
  AND json_extract(p.data, '$.tool') = 'bash'
  AND json_extract(p.data, '$.state.status') = 'completed'
  AND json_extract(p.data, '$.state.output') LIKE '%error%'
  AND m.time_created > (strftime('%s', 'now') - 7*86400) * 1000
GROUP BY substr(json_extract(p.data, '$.state.output'), 1, 200)
HAVING occurrences > 1
ORDER BY occurrences DESC
LIMIT 10;

Find actual tool failures (any tool, last 7 days):

SELECT json_extract(p.data, '$.tool') as tool,
       substr(json_extract(p.data, '$.state.error'), 1, 200) as error_msg,
       COUNT(*) as occurrences,
       GROUP_CONCAT(DISTINCT m.session_id) as sessions
FROM part p
JOIN message m ON m.id = p.message_id AND m.session_id = p.session_id
WHERE json_extract(p.data, '$.type') = 'tool'
  AND json_extract(p.data, '$.state.status') = 'error'
  AND m.time_created > (strftime('%s', 'now') - 7*86400) * 1000
GROUP BY json_extract(p.data, '$.tool'), substr(json_extract(p.data, '$.state.error'), 1, 200)
HAVING occurrences > 1
ORDER BY occurrences DESC
LIMIT 10;

Search strategies

GoalStrategy
Find a user's stated rule/preferenceSearch user text parts for '%always%', '%never%', '%remember%', '%rule%'
Find a design decisionSearch '%decided%', '%tradeoff%', '%reason%' in user text
Find a specific file path or commandLIKE match on tool output/error
Find repeated workflowsGroup tool call sequences by session, look for recurring tool×N patterns
Verify a memory claimFind the session_id from the memory entry [ses_xxx], then query its full execution chain
Count tool usageGROUP BY json_extract(p.data, '$.tool') with COUNT

Constraints

  • Read-only: Never modify the database. Always sqlite3 -readonly or SELECT only.
  • Performance: The DB can be multi-GB. Always use LIMIT and filter by session_id or time_created range.
  • Privacy: Raw trajectory contains everything the user typed. Treat it with care.
  • JSON access: Part data is JSON-in-a-column. Always use json_extract() for structured field access.
Repository
XiaomiMiMo/MiMo-Code
Path

packages/opencode/src/skill/builtin/.bundle/memory-search/SKILL.md

Commit

f0293bf

Last updated
First committed

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.

Claim skill