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/c9r-io/orchestrator/performance-testingnpx skills add c9r-io/orchestrator --skill performance-testinggit clone --depth 1 https://github.com/c9r-io/orchestratorWrote 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/c9r-io/orchestrator/performance-testing)<a href="https://agentmods.dev/skills/c9r-io/orchestrator/performance-testing"><img src="https://agentmods.dev/badge/skills/c9r-io/orchestrator/performance-testing.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.00438 |
| Opus 5 | $0.00020 | $0.00219 |
| Sonnet 5 | $0.00008 | $0.00088 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
performance-testing 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 3d 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
Performance Testing
Benchmark the same revision, configuration, data shape, command, and transport before and after a change. Do not compare debug and release builds.
Choose a Real Surface
For this repository:
- CLI/daemon latency: time a read-only command such as
orchestrator task list -o jsonagainst the same daemon and data set. - Scheduler behavior: use deterministic mock agents under
fixtures/manifests/bundles/; do not use live AI benchmark manifests without explicit approval because they consume external credits. - Slack gateway HTTP baseline: when
orchestrator-slack-gatewayis explicitly running, its health endpoint is/healthz. - Web UI performance: use the tooling declared by
gui/package.jsonand a production build when rendering cost is the target.
Use hyperfine for command latency when installed. Otherwise run a bounded shell loop with /usr/bin/time and preserve raw samples.
HTTP Load Checks
Use hey only after the user identifies a reachable, non-production target and safe endpoint. Start with a cheap health endpoint and a low request/concurrency bound, then increase deliberately:
hey -n 200 -c 10 http://127.0.0.1:8080/healthz
Never guess API routes, credentials, or a Docker Compose environment. A generated project may carry docker/docker-compose.yml; a benchmark script is usable only when the target repository actually owns one.
Evidence
Record:
- pinned git revision and release/debug build mode
- target command or URL, payload, data size, and transport
- sample count and concurrency
- throughput, p50/p90/p99 latency, and error rate
- warm-up policy and machine/load caveats
Treat a regression as actionable only after repeating both baseline and candidate under comparable conditions. Report raw evidence and avoid universal QPS ratings detached from the tested workload.
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.
- 3d ago First seen · 42 lines · 41 tokens per session scan A f6064dd5fe49
performance-testing is a skill published in the GitHub repository c9r-io/orchestrator (21 stars, last pushed 8d ago), licensed MIT. It adds 41 tokens to every session and 438 once invoked, about $0.0002 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 skills, from other repositories
api-design-patterns
Comprehensive API design patterns covering REST, GraphQL, gRPC, versioning, authentication, and modern API best practices.
ppt-review
Read this skill only after current officereview structural output and relevant rendered images exist. Do not use source code, a tool success flag, or the first-slide preview as a substitute for deck evidence.
helmor-debug-operate
Operate, reproduce, and debug a running local Helmor desktop development build through the Tauri MCP bridge. Use when the user asks to use Tauri MCP, towery MCP, the local dev build, the Tauri webview, visual end-to-end validation, UI automation, screenshots, DOM/accessibility snapshots, IPC or log tracing…
review
5-pass structured code review — correctness, security, performance, readability, consistency.
marshal
Meta-orchestrator that takes any direction — broad, specific, or vague — and autonomously chains skills and context into actionable work. Gathers context from codebase, docs, and memory. Only asks the user when it genuinely cannot proceed. Single-session orchestrator.
wiki
Markdown-first knowledge base where the LLM acts as librarian. Ingests raw sources, compiles and interlinks topic files, self-maintains an index. No vector DB or embeddings required -- uses LLM-native navigation over structured markdown up to 400K words.