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/gopherguides/gopher-ai/benchgit clone --depth 1 https://github.com/gopherguides/gopher-aiWhat 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 | $0.00010 | $0.01596 |
| Opus 5 | $0.00005 | $0.00798 |
| Sonnet 5 | $0.00002 | $0.00319 |
| Haiku 4.5 | $0.00001 | $0.00160 |
Grade A, and why
bench 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
If $ARGUMENTS is empty or not provided:
Usage: /bench <target>
/bench pkg/auth/login.go— benchmark all exported functions in a file/bench ProcessOrder— benchmark a specific function/bench pkg/utils/— benchmark all functions in a package
Workflow: detect tooling/existing benchmarks → analyze target → generate table-driven benchmarks → run with -benchmem -count=6 → compare against baseline (if benchstat) → profile CPU + memory → summarize + suggest optimizations.
Ask: "What file, function, or package would you like me to benchmark?"
If $ARGUMENTS is provided:
Generate and run Go benchmarks for the specified code with statistical rigor.
Loop Initialization
!if [ ! -x "${CLAUDE_PLUGIN_ROOT}/scripts/setup-loop.sh" ]; then echo "ERROR: Plugin cache stale. Run /gopher-ai-refresh (or refresh-plugins.sh) and restart Claude Code."; exit 1; else "${CLAUDE_PLUGIN_ROOT}/scripts/setup-loop.sh" "bench" "COMPLETE"; fi
Configuration
- Target:
$ARGUMENTS(file, function, or package)
Steps
1. Detect Benchmark Environment
which benchstat 2>/dev/null && echo "benchstat: available" || echo "benchstat: not found"
grep -rl 'func Bench' --include='*_test.go' ./path/to/package/
ls .bench-baseline*.txt 2>/dev/null
Also detect: existing _test.go patterns, testify vs stdlib, existing .pprof files.
If existing benchmarks for the target, ask via AskUserQuestion:
| Option | Action |
|---|---|
| Run existing | Run only, skip generation |
| Augment | Add new cases alongside existing |
| Generate fresh | Create new benchmarks in a separate file |
2. Analyze Target
Read the target and extract: function signatures, input types/sizes (for realistic data), dependencies/interfaces (for setup), I/O operations (special handling), allocation-heavy patterns (string concat, slice append, map ops), concurrency patterns (channels, mutexes).
For each function: classify CPU- vs memory- vs I/O-bound; identify variable-size sub-benchmarks; need for b.ResetTimer(); exported vs unexported (affects test package choice).
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 · 178 lines · 10 tokens per session scan A c0da81fb29b9
bench is a command published in the GitHub repository gopherguides/gopher-ai (21 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 1,596 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.