Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/xsovad06/sova/benchmark-reportgit clone --depth 1 https://github.com/xsovad06/sovaWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00012 | $0.02841 |
| Opus 5 | $0.00006 | $0.01421 |
| Sonnet 5 | $0.00002 | $0.00568 |
| Haiku 4.5 | $0.00001 | $0.00284 |
Grade A, and why
benchmark-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 308 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark Report
Aggregate benchmark data from interactive sessions (JSONL logs) and SOVA autonomous runs (DB), then generate a velocity comparison report.
Arguments: $ARGUMENTS
Instructions
Step 1: Parse Arguments
Extract optional flags from $ARGUMENTS:
--since YYYY-MM-DD: only include data from sessions after this date--issues N,N,N: only include these specific issue numbers (comma-separated)--update-docs: write the report todocs/benchmark-results.md(default: terminal output only)
If $ARGUMENTS is empty or contains none of these flags, use all available data and output to terminal only.
Step 2: Collect Interactive Data (JSONL)
Find all benchmark log files:
ls .claude/benchmark/issue-*.jsonl 2>/dev/null
If no files exist, note "No interactive benchmark data found" and skip to Step 3.
For each file:
- Extract the issue number from the filename. Files named
issue-null.jsonlor with non-numeric IDs: count them in the file summary but exclude from per-issue metrics. - If
--issueswas specified, skip files whose issue number is not in the list. - If
--sincewas specified, check the firstsession_startevent'stsfield; skip the file if it predates the cutoff.
For each included issue file, extract metrics using jq:
Wall clock (total across all sessions):
jq -s '
[.[] | select(.event == "session_start") | .ts] | first as $start |
[.[] | select(.event == "session_end" or .event == "session_summary") | .ts] | last as $end |
{start: $start, end: $end}
' .claude/benchmark/issue-{N}.jsonl
For multi-session issues (multiple session_start/session_end pairs), sum the durations of each session separately.
Human idle time:
jq -s '
[.[] | select(.event == "human_idle_start" or .event == "human_idle_end")]
| [range(0; length; 2) as $i | (.[($i+1)].ts | split("T") | .[1] | split("Z") | .[0]) as $end_t |
(.[$i].ts | split("T") | .[1] | split("Z") | .[0]) as $start_t |
{start: .[$i].ts, end: .[($i+1)].ts}]
' .claude/benchmark/issue-{N}.jsonl
Compute human idle as the sum of all human_idle_start to human_idle_end intervals (in minutes). If an odd number of idle events exists (unclosed idle period), ignore the unpaired event.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 308 lines · 12 tokens per session scan A 0ebef99d38f9
benchmark-report is a command published in the GitHub repository xsovad06/sova (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 12 tokens to every session and 2,841 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
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dashboard
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update
Check for and apply KARIMO updates from GitHub releases.
implement-fix
Minimal pipeline for test-fixing tasks.
create-issue
Create GitHub issue with automated research (--quick for fast mode).