lading is a data-generation and load-testing tool that measures the performance and resource behavior of long-running programs by sending them repeatable synthetic workloads. Developers and performance engineers use it to test daemons and other complex programs across different protocols, including in Datadog Agent regression testing. The catalogue skills and instruction support working with lading.
Borrowing it
Nothing to install: this file belongs to DataDog/lading. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/DataDog/lading/main/.claude/skills/lading-optimize-hunt/SKILL.mdgit clone --depth 1 https://github.com/DataDog/ladingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/datadog/lading/lading-optimize-hunt)<a href="https://agentmods.dev/skills/datadog/lading/lading-optimize-hunt"><img src="https://agentmods.dev/badge/skills/datadog/lading/lading-optimize-hunt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/datadog/lading/lading-optimize-hunt"><img src="https://agentmods.dev/badge/skills/datadog/lading/lading-optimize-hunt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00026 | $0.01037 |
| Opus 5.5 | $0.00010 | $0.00415 |
| Sonnet 5.5 | $0.00005 | $0.00207 |
| Haiku 4.5 | $0.00003 | $0.00104 |
Grade D, and why
lading-optimize-hunt scanned grade D with 2 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 2mo 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
allowed-tools: Bash(cat:*) Bash(cargo:*) Bash(ci/*:*) Bash(hyperfine:*) Bash(*/payloadtool:*) Bash(tee:*) Read Write Edit Glob Grep Skill Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf target/criterion How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Optimization Hunt
Coordinates optimization attempts: captures baselines, implements changes, invokes review, and records all outcomes.
Role: Coordinator and Recorder
Hunt is the coordinator and recorder — it captures baselines, implements changes, hands off to review, and records all outcomes.
Hunt does NOT:
- Run post-change benchmarks (review does this)
- Make pass/fail decisions on optimizations (review does this)
Hunt DOES:
- Record all verdicts and outcomes in
.claude/skills/lading-optimize-hunt/assets/db.yamlafter review returns
Phase 0: Pre-flight
Run /lading-preflight.
Phase 1: Find Target
Run /lading-optimize-find-target.
It returns a YAML block with 6 fields: pattern, technique, target, file, bench, fingerprint - Print it out.
Phase 2: Establish Baseline
CRITICAL: Capture baseline metrics BEFORE making any code changes.
Identify the Benchmark Target
Use the bench and fingerprint fields from find-target's output — they are repo-relative paths ready to use:
BENCH=<bench field without extension> # e.g. from "lading_payload/benches/syslog.rs" use "--bench syslog"
PAYLOADTOOL_CONFIG=<fingerprint field> # e.g. "ci/fingerprints/syslog/lading.yaml"
Stage 1: Clear previous benchmarks
Clear any previously captured baselines so stale data cannot contaminate this run.
rm -f /tmp/criterion-baseline.log /tmp/baseline.json /tmp/baseline-mem.txt
rm -rf target/criterion
Stage 2: Micro-benchmark Baseline
Run only the benchmark for your target:
cargo criterion --bench "$BENCH" 2>&1 | tee /tmp/criterion-baseline.log
Stage 3: Macro-benchmark Baseline
Use the matching fingerprint config:
cargo build --release --bin payloadtool
hyperfine --warmup 3 --runs 30 --export-json /tmp/baseline.json \
"./target/release/payloadtool $PAYLOADTOOL_CONFIG"
./target/release/payloadtool "$PAYLOADTOOL_CONFIG" --memory-stats 2>&1 | tee /tmp/baseline-mem.txt
What ships with it
8 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.
- assets/db.yaml 1.1 KB
- assets/db/cache-inline.yaml 2.1 KB
- assets/db/datadog-logs-buffer-reuse.yaml 1.2 KB
- assets/db/dogstatsd-buffer-reuse.yaml 1.5 KB
- assets/db/fluent-on-demand-serialization.yaml 3.6 KB
- assets/db/syslog-to_bytes-reusable-buffer.yaml 2.4 KB
- assets/index.template.yaml 186 B
- README.md 15 KB
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.
- 2mo ago First seen · 137 lines · 26 tokens per session scan D 026256f992fc
lading-optimize-hunt is a skill published in the GitHub repository DataDog/lading (101 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 1,037 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it D with 2 findings (unrestricted tool access, recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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