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/codspeedhq/codspeed/codspeed-setup-harnessnpx skills add CodSpeedHQ/codspeed --skill codspeed-setup-harnessgit clone --depth 1 https://github.com/CodSpeedHQ/codspeedWhat 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 | $0.00120 | $0.02305 |
| Opus 5 | $0.00060 | $0.01153 |
| Sonnet 5 | $0.00024 | $0.00461 |
| Haiku 4.5 | $0.00012 | $0.00231 |
Grade A, and why
codspeed-setup-harness 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 — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Setup Harness
You are a performance engineer helping set up benchmarks and CodSpeed integration for a project. Your goal is to create useful, representative benchmarks and wire them up so CodSpeed can measure and track performance.
Step 1: Analyze the project
Before writing any benchmark code, understand what you're working with:
-
Detect the language and build system: Look at the project structure, package files (
Cargo.toml,package.json,pyproject.toml,go.mod,CMakeLists.txt), and source files. -
Identify existing benchmarks: Check for benchmark files,
codspeed.yml, CI workflows mentioning CodSpeed or benchmarks. -
Identify hot paths: Look at the codebase to understand what the performance-critical code is. Public API functions, data processing pipelines, I/O-heavy operations, and algorithmic code are good candidates.
-
Check CodSpeed auth: Ensure
codspeed auth loginhas been run.
Step 2: Choose the right approach
Based on the language and what the user wants to benchmark, pick the right harness:
Language-specific harnesses (recommended when available)
These integrate deeply with CodSpeed and provide per-benchmark flamegraphs, fine-grained comparison, and simulation mode support.
| Language | Framework | How to set up |
|---|---|---|
| Rust | divan (recommended), criterion, bencher | Add codspeed-<framework>-compat as dependency using cargo add --rename |
| Python | pytest-benchmark | Install pytest-codspeed, use @pytest.benchmark or benchmark fixture |
| Node.js | vitest (recommended), tinybench v5, benchmark.js | Install @codspeed/<framework>-plugin, configure in vitest/test config |
| Go | go test -bench | No packages needed — CodSpeed instruments go test -bench directly |
| C/C++ | Google Benchmark | Build with CMake, CodSpeed instruments via valgrind-codspeed |
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 · 322 lines · 120 tokens per session scan A a0058960f044
codspeed-setup-harness is a skill published in the GitHub repository CodSpeedHQ/codspeed (281 stars, last pushed today), licensed Apache-2.0. It adds 120 tokens to every session and 2,305 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 2026-08-30.
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