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.
git clone --depth 1 https://github.com/Project-VIC-International/Agentic-AI-Development-CourseWrote 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/rules/project-vic-international/agentic-ai-development-course/no-stubs)<a href="https://agentmods.dev/rules/project-vic-international/agentic-ai-development-course/no-stubs"><img src="https://agentmods.dev/badge/rules/project-vic-international/agentic-ai-development-course/no-stubs/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/rules/project-vic-international/agentic-ai-development-course/no-stubs"><img src="https://agentmods.dev/badge/rules/project-vic-international/agentic-ai-development-course/no-stubs.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 | $0.01050 | $0.01050 |
| Opus 5 | $0.00525 | $0.00525 |
| Sonnet 5 | $0.00210 | $0.00210 |
| Haiku 4.5 | $0.00105 | $0.00105 |
Grade A, and why
no-stubs 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 9d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
No Stubs
Never create stub implementations, placeholder functions, mock returns, or TODO-laden skeletons that pretend to work. Every function, CLI command, API endpoint, MCP tool handler, and AI prompt template MUST contain real, working logic that performs its documented purpose end to end.
Why This Matters
In law enforcement and digital forensics work, a tool that says it did something but actually did nothing is worse than a tool that admits it cannot help. A stubbed-out CSAM hash check that quietly returns "no matches" misses real evidence. A stubbed-out audit logger that returns success but writes nothing leaves an investigator unable to prove what happened during examination. A stubbed-out CASE/UCO export that returns empty JSON-LD breaks interoperability with every downstream tool — silently.
Stubs are technical debt that masquerades as progress. In this domain, they are also a defensibility risk.
The Rules
- If a function is defined, it must do what its name and docstring say.
- If a CLI command is registered, running it must produce its documented output (or a clear, actionable error explaining why it cannot).
- If an API endpoint is wired up, calling it must return the real result — not
{"status": "ok"}with no work performed. - If an MCP tool descriptor is published, the tool MUST execute the action an AI agent would expect from reading the schema.
- If a dependency, model, hash database, or external service is not yet available, surface an actionable error (e.g.,
"VICS hash database not loaded — run 'tool init --vics-path PATH' first") instead of returning a fake "acknowledged" response. - Test with realistic synthetic data, not with values that bypass the logic. A test that hard-codes
assert classify(image) == "category-1"without actually running the classifier proves nothing.
What Counts as a Stub (and Is Forbidden)
passorreturn Nonein a function body that is documented to do workreturn {"results": []}from a search endpoint that has not been implementedraise NotImplementedErrorshipped in a release branch (acceptable on a feature branch only when the spec explicitly defers the function to a later milestone and the deferral is documented)# TODO: implementleft in code that has been committed past the design phase- An ingest module registered in the module registry that does not actually parse anything
- A CASE/UCO export function that emits the
@contextbut no@graphcontent - A "validation" step that always returns "valid" because the validator hasn't been wired up
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.
- 9d ago First seen · 62 lines · 1,050 tokens per session scan A 7fc67fea3fad
no-stubs is a cursor rule published in the GitHub repository Project-VIC-International/Agentic-AI-Development-Course (5 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 1,050 tokens to every session, about $0.0052 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.
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