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/sunholo-data/ailang-parse/benchmarknpx skills add sunholo-data/ailang-parse --skill benchmarkgit clone --depth 1 https://github.com/sunholo-data/ailang-parseWhat 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 | $0.00115 | $0.01498 |
| Opus 5 | $0.00057 | $0.00749 |
| Sonnet 5 | $0.00023 | $0.00300 |
| Haiku 4.5 | $0.00012 | $0.00150 |
Grade A, and why
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 yesterday.
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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark
Run OfficeDocBench, regenerate summary.json (the single source of truth for benchmark numbers across the website), and verify the docs site stays in sync.
Why this skill exists
OfficeDocBench scores live in one place: benchmarks/officedocbench/results/summary.json. From there they propagate to the static site via docs/data/officedocbench-summary.json (a mirror) and the data-bench injector at docs/js/bench-data.js. If you re-run the benchmark without using this skill, you risk:
- Forgetting to regenerate the summary mirror in
docs/ - Forgetting that JSON-LD / SEO copy on a handful of pages cannot use
data-benchand must be hand-edited if the AILANG Parse composite changes - Not catching score regressions before committing
This skill bundles all of those steps so they happen together.
Three modes
| When | Use script | What it does |
|---|---|---|
| Changed parser code, want to re-verify everything | scripts/full.sh |
Full eval across all 8 adapters (~1 minute), regenerates summary, syncs docs |
| Changed parser code, only care about AILANG Parse | scripts/quick.sh |
docparse-only eval (~10 sec), regenerates summary, syncs docs |
Just want to refresh summary.json from existing per-adapter results without re-parsing |
scripts/refresh-summary.sh |
Re-aggregates the existing results/<adapter>/results.json files into a fresh summary.json + mirror |
After any of these, the script automatically:
- Diffs the new AILANG Parse composite score against the previous run
- If the composite changed, prints a checklist of static-copy files that need manual updates (since they can't use
data-bench) - Reports the headline numbers so you can sanity-check before committing
Quick start
# Standard: re-run all adapters and refresh the site
.claude/skills/benchmark/scripts/full.sh
# Fast iteration: only re-run AILANG Parse
.claude/skills/benchmark/scripts/quick.sh
# Just regenerate summary.json from existing results (no parsing)
.claude/skills/benchmark/scripts/refresh-summary.sh
What ships with it
5 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.
- yesterday First seen · 118 lines · 115 tokens per session scan A 1375f1f5a687
benchmark is a skill published in the GitHub repository sunholo-data/ailang-parse (0 stars, last pushed yesterday), licensed Apache-2.0. It adds 115 tokens to every session and 1,498 once invoked, about $0.0006 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.
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