Context usage

Skill jmylchreest/aide/skills/context-usage

Analyze current session context and token usage from OpenCode SQLite databaseFrom its SKILL.md

Install

npx -y skills add jmylchreest/aide --skill context-usage

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SKILL.md

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Context Usage Analysis

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.

Prerequisites

This skill only works on OpenCode. Verify by checking the environment:
- $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)
The OpenCode database is at ~/.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.

Workflow

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.

Step 1: Validate environment

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.

Step 2: Session overview

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';
"

Step 3: Token totals

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';
"

Step 4: Tool output breakdown

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;
"

Step 5: Total session size

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';
"

Output Format

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.