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 skills add causify-ai/helpers --skill testing.fix_mock_testsgit clone --depth 1 https://github.com/causify-ai/helpersWrote 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/causify-ai/helpers/testing.fix_mock_tests)<a href="https://agentmods.dev/skills/causify-ai/helpers/testing.fix_mock_tests"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/testing.fix_mock_tests/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/skills/causify-ai/helpers/testing.fix_mock_tests"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/testing.fix_mock_tests.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 3 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
- medium Data Exfiltration · line 32 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 42 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00006 | $0.00919 |
| Opus 5.5 | $0.00002 | $0.00368 |
| Sonnet 5.5 | $0.00001 | $0.00184 |
| Haiku 4.5 | $0.00001 | $0.00092 |
Grade A, and why
testing.fix_mock_tests scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
return requests.get(f"https://api.com/users/{user_id}").json() How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal
- When the user passes a test file, apply the following transformations to remove mocking from unit testing code without changing behavior
- Mocking often signals that your design could be more modular
- Avoiding mocking in Python unit tests means designing code so dependencies are easy to control naturally, rather than being intercepted artificially
Workflow
- Avoid mocking using the strategies below
Prefer Pure Functions
- Functions that depend only on inputs and return outputs are trivial to test
- Example:
def add(a: int, b: int) -> int: return a + b
- Example:
- No mocking needed because there are no external dependencies
Design for Dependency Injection (DI)
- Instead of hard coding dependencies inside functions or classes, pass them in
- Bad (hardcodes the dependency, forcing a mock to test it)
from typing import Any import requests def get_user(user_id: int) -> Any: return requests.get(f"https://api.com/users/{user_id}").json() - Good (injects the dependency, so a fake can be substituted in tests)
from typing import Any, Protocol class HttpClient(Protocol): def get(self, url: str) -> Any: ... def get_user(user_id: int, http_client: HttpClient) -> Any: return http_client.get(f"https://api.com/users/{user_id}").json() - Bad (creates its own dependency inside
__init__)class Database: pass class UserService: def __init__(self) -> None: self.db: Database = Database() - Good (accepts the dependency, so a fake can be passed in)
class Database: pass class UserService: def __init__(self, db: Database) -> None: self.db: Database = db
Create Lightweight Fakes Instead of Mocks
- A fake is a real implementation with simplified behavior
- More maintainable and less brittle than mocks
- Example:
from typing import Any class FakeDatabase: def __init__(self) -> None: self.data: dict[str, Any] = {} def save(self, key: str, value: Any) -> None: self.data[key] = value def get(self, key: str) -> Any: return self.data.get(key)
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.
- 1mo ago Changed · +6 lines 9c095897d3db
- 1mo ago First seen · 119 lines · 6 tokens per session scan A 070e7518068b
testing.fix_mock_tests is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 6 tokens to every session and 919 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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When delegating a task affected by this skill, include.