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From aide
Analyzes OpenCode session context usage, token consumption, LLM turns, and costs by querying SQLite database. Requires OpenCode environment and sqlite3.
npx claudepluginhub jmylchreest/aide --plugin aideHow this skill is triggered — by the user, by Claude, or both
Slash command
/aide:context-usageThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**Recommended model tier:** balanced (sonnet) - straightforward SQL queries
Provides behavioral guidelines to reduce common LLM coding mistakes, focusing on simplicity, surgical changes, assumption surfacing, and verifiable success criteria.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Guides systematic root-cause debugging when tests fail, builds break, or unexpected errors occur. Provides a structured triage checklist to preserve evidence, localize, and fix issues instead of guessing.
Share bugs, ideas, or general feedback.
Recommended model tier: balanced (sonnet) - straightforward SQL queries
Analyze the current session's context window consumption, tool usage breakdown, and token costs by querying the OpenCode SQLite database directly.
$OPENCODE=1 — set by the OpenCode runtime$AIDE_PLATFORM=opencode — set by aide when running under OpenCode$AIDE_SESSION_ID — the current session ID (injected by aide)~/.local/share/opencode/opencode.db.sqlite3 must be available on the system.If $OPENCODE is not 1 or $AIDE_PLATFORM is not opencode, abort immediately
and inform the user that this skill is only supported on OpenCode.
Do not attempt to query other databases (e.g. Claude Code's storage) — the
schema is OpenCode-specific.
If $AIDE_SESSION_ID is not set, abort with a message explaining that the
session ID could not be determined.
Run the following queries sequentially in a single Bash call (chain with &&).
Present results to the user in a formatted summary after all queries complete.
test "$OPENCODE" = "1" && echo "Platform: OpenCode" || echo "ERROR: Not running on OpenCode (OPENCODE=$OPENCODE)"
test "$AIDE_PLATFORM" = "opencode" && echo "AIDE Platform: opencode" || echo "WARNING: AIDE_PLATFORM=$AIDE_PLATFORM"
test -n "$AIDE_SESSION_ID" && echo "Session: $AIDE_SESSION_ID" || echo "ERROR: AIDE_SESSION_ID not set"
If OPENCODE is not 1, stop immediately — this skill cannot work outside OpenCode.
If AIDE_SESSION_ID is not set, stop and inform the user.
sqlite3 ~/.local/share/opencode/opencode.db "
SELECT
s.title,
s.slug,
ROUND((julianday('now') - julianday(datetime(s.time_created/1000, 'unixepoch'))) * 24, 1) as hours_old,
(SELECT COUNT(*) FROM message m WHERE m.session_id = s.id) as messages,
CASE WHEN s.time_compacting IS NOT NULL THEN 'yes' ELSE 'no' END as compacted
FROM session s
WHERE s.id = '$AIDE_SESSION_ID';
"
Sum tokens from step-finish parts (each represents one LLM turn):
sqlite3 ~/.local/share/opencode/opencode.db "
SELECT
SUM(json_extract(data, '$.tokens.input')) as input_tokens,
SUM(json_extract(data, '$.tokens.output')) as output_tokens,
SUM(json_extract(data, '$.tokens.cache.read')) as cache_read_tokens,
SUM(json_extract(data, '$.tokens.cache.write')) as cache_write_tokens,
SUM(json_extract(data, '$.tokens.total')) as total_tokens,
COUNT(*) as llm_turns
FROM part
WHERE session_id = '$AIDE_SESSION_ID'
AND json_extract(data, '$.type') = 'step-finish';
"
Show tool usage ranked by total output size:
sqlite3 ~/.local/share/opencode/opencode.db "
SELECT
json_extract(data, '$.tool') as tool,
COUNT(*) as calls,
SUM(length(json_extract(data, '$.state.output'))) as total_output_bytes,
ROUND(AVG(length(json_extract(data, '$.state.output')))) as avg_bytes,
MAX(length(json_extract(data, '$.state.output'))) as max_bytes
FROM part
WHERE session_id = '$AIDE_SESSION_ID'
AND json_extract(data, '$.type') = 'tool'
GROUP BY tool
ORDER BY total_output_bytes DESC;
"
sqlite3 ~/.local/share/opencode/opencode.db "
SELECT
SUM(length(json_extract(data, '$.state.output'))) as tool_output_bytes,
SUM(length(json_extract(data, '$.state.input'))) as tool_input_bytes,
SUM(length(data)) as total_part_bytes
FROM part
WHERE session_id = '$AIDE_SESSION_ID'
AND json_extract(data, '$.type') = 'tool';
"
Present the results as a structured summary:
## Session Context Usage
**Session:** <title> (<slug>)
**Age:** <hours> hours | **Messages:** <count> | **Compacted:** yes/no
### Token Usage
| Metric | Count |
|--------|-------|
| Input tokens | <n> |
| Output tokens | <n> |
| Cache read | <n> |
| Cache write | <n> |
| **Total tokens** | **<n>** |
| LLM turns | <n> |
### Tool Output Breakdown (by total bytes)
| Tool | Calls | Total Output | Avg/call | Max |
|------|-------|-------------|----------|-----|
| ... | ... | ... | ... | ... |
### Session Size
- Tool outputs: <n> KB
- Tool inputs: <n> KB
- Total part storage: <n> KB (includes JSON metadata overhead)
Format byte values as KB (divide by 1024, round to 1 decimal). Highlight the top 3 tools by total output as the biggest context consumers. If any single tool call exceeds 20KB, flag it as a potential optimization target.