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.reach_coveragegit 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.reach_coverage)<a href="https://agentmods.dev/skills/causify-ai/helpers/testing.reach_coverage"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/testing.reach_coverage/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.reach_coverage"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/testing.reach_coverage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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.
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 | $0.00013 | $0.00602 |
| Opus 5.5 | $0.00005 | $0.00241 |
| Sonnet 5.5 | $0.00003 | $0.00120 |
| Haiku 4.5 | $0.00001 | $0.00060 |
Grade A, and why
testing.reach_coverage 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal
- Given the passed function, file, or files
<FILES>, increase unit test coverage from the corresponding files<TEST_FILES>to approach 100 percent using a plan-then-implement approach
Workflow
Establish Current Coverage
-
Identify the test files corresponding to the target function, file, files
<TEST_FILES>using the rules- E.g.,
helpers/hllm_cli.py -> helpers/test/test_hllm_cli.py
- E.g.,
-
Print the files to test
Target files: <FILES> Test files: <TEST_FILES> -
Run the following command and record the results:
# Using invoke (preferred): > i run_coverage --suite fast --generate-html-report # Or directly with pytest inside Docker: > pytest --cov=<PKG> --cov-report=term-missing --cov-report=html <TEST_FILE> -
Summarize which lines and branches are not covered
Design a Testing Plan
- Analyze uncovered code paths and behaviors
- Propose a clear testing plan that:
- Tests functions modularly before testing interactions
- Prioritizes end-to-end and user-visible behavior over incidental implementation details
- Avoids testing assertions, defensive checks, or invalid inputs unless they are critical to correctness
- Explicitly map each uncovered area to one or more proposed tests
Specify Tests Without Implementation
- Define test classes and test method names
- For each proposed test:
- Describe the input data
- Describe the expected output or observable behavior
- Do not write executable test code at this stage
Implement After Approval
- Wait for user confirmation or feedback on the testing plan
- After approval:
- Implement the tests according to the approved plan
- Re-run coverage and verify that coverage for the target function is near 100 percent
- Report final coverage results and remaining gaps, if any
Important Rules
- Do not implement tests before the plan is approved
- Do not proceed if instructions or requirements are ambiguous
- Always adhere to the formatting and style guides referenced above
- Focus on meaningful behavior and correctness rather than superficial coverage
- All tests and code must strictly follow:
.claude/skills/coding.rules.mdfor any Python code.claude/skills/testing.rules.mdfor tests
- If any part of the task is unclear or underspecified, stop and ask for clarification before proceeding
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 · +7 lines · -3 tokens per session 2de4759ab541
- 1mo ago First seen · 68 lines · 16 tokens per session scan A b1c7ec84d189
testing.reach_coverage is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 13 tokens to every session and 602 once invoked, about $0.0001 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 2026-09-03.
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