benchmark-test

benchmark-test is a skill for Claude Code, Codex from onixhdz/cartograph. It costs 32 tokens per session (5,269 once invoked), scanned A, original, MIT.

A repeatable test system for measuring Cartograph's code-search quality across languages and query types. Cartograph is a tool that indexes code and helps find symbols and relationships in a repository.

In plain words
What is it for?
Use it to build test batteries, index sample repositories, run keyword and intent searches, score results, and detect drops in search quality.
Why use it?
It shows whether changes to search, indexing, or text-embedding code improve results or cause regressions. It uses fixed test questions and expected answers so results can be compared over time.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Install

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.

agentmods
npx agentmods add skills/onixhdz/cartograph/benchmark-test
Any agent
npx skills add onixhdz/cartograph --skill benchmark-test
Clone the repo
git clone --depth 1 https://github.com/onixhdz/cartograph

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for benchmark-test

README.md
[![agentmods](https://agentmods.dev/badge/skills/onixhdz/cartograph/benchmark-test.svg)](https://agentmods.dev/skills/onixhdz/cartograph/benchmark-test)
Your own site
<a href="https://agentmods.dev/skills/onixhdz/cartograph/benchmark-test"><img src="https://agentmods.dev/badge/skills/onixhdz/cartograph/benchmark-test.svg" alt="Measured on agentmods" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,269 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.05269
Opus 5 $0.00016 $0.02635
Sonnet 5 $0.00006 $0.01054
Haiku 4.5 $0.00003 $0.00527

Measured 6d ago against content hash 9d725e9b6d05, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

benchmark-test 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 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (score.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/benchmark-test/SKILL.md · 549 lines

How it starts

The opening of the file, as written. The whole thing — 549 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cartograph Search Quality Benchmark

Systematic evaluation framework for measuring and improving Cartograph's search quality across keyword and intent queries. Used to validate changes to the embedding pipeline (textgen.go), hybrid search (backend.go), and ingestion (entry_point_scoring.go) without regression.

Quick Start — Run All Batteries

# Prerequisites: dev binary built, server running
task build:dev
./cartograph-darwin-arm64 serve start --no-detach --no-idle &

# 1. Index all test repos (clean + re-embed)
for repo in turbot/steampipe excalidraw/excalidraw fastapi/fastapi hashicorp/nomad gatling/gatling; do
  ./cartograph-darwin-arm64 clean "$repo"
  ./cartograph-darwin-arm64 analyze "$repo" --embed=sync
done

# 2. Run batteries (see "Running a Battery" below for per-repo commands)
# 3. Score with score.py (see "Scoring" below)

Architecture of the Benchmark

Battery Files

Each test project has a battery file in batteries/ defining 5 investigations with keyword + intent query pairs and ground-truth expected symbols:

File Language Nodes Limit Investigations
batteries/steampipe.md Go 882 8 query exec, plugins, db lifecycle, connections, console
batteries/excalidraw.md TypeScript 1253 8 rendering, export, undo/redo, collaboration, elements
batteries/fastapi.md Python 756 8 routing, DI, validation, middleware, OpenAPI
batteries/nomad.md Go 37587 15 startup, scheduling, node failure, raft, client-server
batteries/gatling.md Scala 11863 10 simulation exec, HTTP protocol, session/stats, actions, assertions
batteries/gatling-usecases.md Scala 11863 10 redirects, throttling, CSV feeding, reporting, WebSocket, session state
batteries/mdbook.md Rust 2375 8 CLI dispatch, build pipeline, preprocessors, config/init, serve/watch

Read the full file on GitHub · 549 lines

Changes

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.

  1. 6d ago First seen · 549 lines · 32 tokens per session scan A 9d725e9b6d05

Subscribe to this mod's changes

benchmark-test is a skill published in the GitHub repository onixhdz/cartograph (11 stars, last pushed 2d ago), licensed MIT. It adds 32 tokens to every session and 5,269 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens