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/postindustria-tech/agentic-toolkit/neograph-dev-test-designnpx skills add postindustria-tech/agentic-toolkit --skill neograph-dev-test-designgit clone --depth 1 https://github.com/postindustria-tech/agentic-toolkitWrote 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/postindustria-tech/agentic-toolkit/neograph-dev-test-design)<a href="https://agentmods.dev/skills/postindustria-tech/agentic-toolkit/neograph-dev-test-design"><img src="https://agentmods.dev/badge/skills/postindustria-tech/agentic-toolkit/neograph-dev-test-design.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 | $0.00076 | $0.01470 |
| Opus 5 | $0.00038 | $0.00735 |
| Sonnet 5 | $0.00015 | $0.00294 |
| Haiku 4.5 | $0.00008 | $0.00147 |
Grade A, and why
neograph-dev-test-design 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.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neograph Test Design
Provides test conventions, file layout, fake infrastructure, and the obligation test matrix pattern for the neograph codebase. The test suite has 1400+ tests across 40 files. This skill prevents the most common testing mistakes.
Test File Layout
Where to put new tests
| Testing... | File | Package |
|---|---|---|
| Assembly-time validation, fan-in, lint | test_validation.py |
root |
| Rendering (BAML, XML, JSON, render_input) | test_renderers.py |
root |
| Sub-constructs, state hygiene | test_composition.py |
root |
| ForwardConstruct | test_forward.py |
root |
| Conditions, condition registry | test_conditions.py |
root |
| Loop modifier | test_loop.py |
root |
| Inline prompts, ${var} resolution | test_inline_prompts.py |
root |
| CLI (neograph check, test-scaffold) | test_cli.py |
root |
| @node decorator basics | decorator/test_basics.py |
decorator/ |
| @node construct assembly | decorator/test_construct_assembly.py |
decorator/ |
| Scripted/think/agent/act modes | modes/test_core_modes.py |
modes/ |
| LLM internals (retry, parsing) | modes/test_llm_internals.py |
modes/ |
| Oracle modifier | modifiers/test_oracle.py |
modifiers/ |
| Each modifier | modifiers/test_each.py |
modifiers/ |
| Property-based topologies | hypothesis/test_topologies.py |
hypothesis/ |
| Structural guards (AST scanning) | test_structural_guards.py |
root |
New tests go in the matching file. If a feature spans multiple files, put the test where the primary behavior lives.
Fake Infrastructure
All fakes live in tests/fakes.py. Do not invent new fakes unless existing
ones genuinely do not cover the case.
from tests.fakes import StructuredFake, StructuredFakeWithRaw, TextFake, ReActFake, configure_fake_llm
# Simple structured output
configure_fake_llm(lambda tier: StructuredFakeWithRaw(lambda m: m(field="value")))
# With capturing prompt compiler
captured = {}
def capturing_compiler(template, data, **kw):
captured[template] = data
return [{"role": "user", "content": "test"}]
configure_fake_llm(
factory=lambda tier: StructuredFakeWithRaw(lambda m: m(result="ok")),
prompt_compiler=capturing_compiler,
)
# ReAct tool loop
configure_fake_llm(lambda tier: ReActFake(
tool_calls=[[{"name": "search", "args": {}, "id": "t1"}], []],
final=lambda m: m(answer="done"),
))
What ships with it
2 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.
- 3d ago First seen · 159 lines · 76 tokens per session scan A c20473bd59c7
neograph-dev-test-design is a skill published in the GitHub repository postindustria-tech/agentic-toolkit (2 stars, last pushed 1mo ago), licensed MIT. It adds 76 tokens to every session and 1,470 once invoked, about $0.0004 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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.
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…