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 skills/docxology/template/benchmarknpx skills add docxology/template --skill benchmarkgit clone --depth 1 https://github.com/docxology/templateWhat 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 | $0.00053 | $0.00403 |
| Opus 5 | $0.00026 | $0.00201 |
| Sonnet 5 | $0.00011 | $0.00081 |
| Haiku 4.5 | $0.00005 | $0.00040 |
Grade A, and why
infrastructure-benchmark 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.
What it actually says
Benchmark Infrastructure
Use infrastructure.benchmark for small, deterministic readiness benchmarks over public template exemplar outputs. The module reads real files, applies explicit manifest checks and optional weighted rubrics, and emits JSON or Markdown score reports.
Common Workflows
uv run python -m infrastructure.benchmark --repo-root .
uv run python -m infrastructure.benchmark \
--repo-root . \
--output-json /tmp/template_benchmark.json \
--output-markdown /tmp/template_benchmark.md
uv run python -m infrastructure.benchmark \
--repo-root . \
--write-default-manifest
Routing Rules
- Keep benchmark manifests scoped to public template exemplars and generated output contracts.
- Use real output files, manuscript sources, evidence registries, and artifact manifests.
- Do not add network calls, LLM calls, mocks, or private-project paths.
- Keep scoring dimensions explicit and exactly aligned with manifest checks so failed checks, weights, and partial scores remain inspectable.
- Treat the default manifest as a fail-closed sweep of the full public roster; never shrink it to make a readiness run green.
Public Imports
BenchmarkManifestBenchmarkCheckResultBenchmarkScoreRubricScoreRubricSetload_benchmark_manifestrun_benchmark_manifestscore_project_against_manifestscore_rubricscores_to_dictscores_to_markdownwrite_default_manifest
Pair this skill with README.md and AGENTS.md for module rules and validation commands.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 49 lines · 53 tokens per session scan A 5c3c59afd03b
infrastructure-benchmark is a skill published in the GitHub repository docxology/template (19 stars, last pushed 2d ago), licensed Apache-2.0. It adds 53 tokens to every session and 403 once invoked, about $0.0003 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.
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