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 signnow/sn-mcp-server --skill sn-testinggit clone --depth 1 https://github.com/signnow/sn-mcp-serverWrote 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/signnow/sn-mcp-server/sn-testing)<a href="https://agentmods.dev/skills/signnow/sn-mcp-server/sn-testing"><img src="https://agentmods.dev/badge/skills/signnow/sn-mcp-server/sn-testing/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/signnow/sn-mcp-server/sn-testing"><img src="https://agentmods.dev/badge/skills/signnow/sn-mcp-server/sn-testing.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 | $0.00081 | $0.01554 |
| Opus 5.5 | $0.00032 | $0.00622 |
| Sonnet 5.5 | $0.00016 | $0.00311 |
| Haiku 4.5 | $0.00008 | $0.00155 |
Grade A, and why
sn-testing 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 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.
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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing Standards
Analyze Protocol
Before writing tests, evaluate each change with the 3 YES criteria — at least one must be met:
- Business Logic: Does the change affect business logic?
- Regression Risk: Is it prone to regression?
- Complexity: Is it complex enough to benefit from tests?
Do not write useless tests. Quality over quantity.
Testing Strategy by Layer
A. Tool Business Logic (sn_mcp_server/tools/<feature>.py)
- Type: Unit. Isolation: Mock
SignNowAPIClientviaMagicMock. Mockfastmcp.ContextviaAsyncMockwhen function acceptsctx. - Focus: Data transformation, curated response fields, edge cases (empty data, missing optionals), error propagation, status normalization.
class TestFeatureName:
"""Test cases for _feature_function."""
@pytest.fixture
def mock_client(self):
"""Create a mock SignNowAPIClient."""
return MagicMock()
def test_feature_happy_path(self, mock_client):
"""Test successful execution with valid data."""
mock_client.api_method.return_value = SampleModel(...)
result = _feature_function(mock_client, "test_token", "param_value")
assert isinstance(result, ExpectedResponseModel)
assert result.field == "expected_value"
mock_client.api_method.assert_called_once_with("test_token", "param_value")
B. Tool Response Models (sn_mcp_server/tools/models.py)
- Type: Unit. Focus: Construction, defaults,
from_*factories, status normalization, edge cases.
class TestResponseModel:
"""Test cases for ResponseModel."""
def test_model_construction_with_defaults(self):
"""Test model handles missing optional fields."""
model = ResponseModel(id="test123", name="Test")
assert model.optional_field is None
@pytest.mark.parametrize("raw_status,expected", [
("sent", "pending"),
("fulfilled", "completed"),
])
def test_status_normalization(self, raw_status, expected):
"""Test raw API status maps to unified status."""
result = InviteStatusValues.from_raw_status(raw_status)
assert result == expected
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 First seen · 174 lines · 81 tokens per session scan A 3e9f7a744a1e
sn-testing is a skill published in the GitHub repository signnow/sn-mcp-server (8 stars, last pushed 2mo ago), licensed MIT. It adds 81 tokens to every session and 1,554 once invoked, about $0.0003 per session on Opus 5.5. 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
pytest-suite
Write or extend the backend test suite following this project's conventions. Use when adding tests for a new service/route/repository, when coverage is missing, or when asked to test a feature. Knows the mocked-session + httpx AsyncClient setup so tests run with no database.
http-load-profiler
Run stepped HTTP load tests with ab/wrk, ramping concurrency levels to collect p50/p90/p99 latency, detect performance inflection points, and recommend optimal concurrency. Triggered by requests like 'load test this URL', 'benchmark my API', 'find the max concurrency', or mentions of p99 latency, throughput…
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Generate comprehensive tests including unit, integration, and property-based tests.
debug
Structured bug diagnosis and fixing workflow that reproduces, diagnoses root cause, applies a minimal fix, writes regression tests, and scans for similar patterns.
itgc-testing
A skill for testing information-technology general controls, which are the basic safeguards around access, system changes, software development, and day-to-day IT operations. It uses the COBIT 2019 governance framework and can also refer to ISO 27001:2022.
uat-testing
Run end-to-end User Acceptance Tests for Agent Brain features. Builds wheels, installs packages, starts a test server, runs tests, and reports results — all without permission prompts.