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 agents/bostonorange/claude-code-framework/test-writergit clone --depth 1 https://github.com/BostonOrange/claude-code-frameworkWhat 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 | $0.00018 | $0.00510 |
| Opus 5 | $0.00009 | $0.00255 |
| Sonnet 5 | $0.00004 | $0.00102 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
test-writer 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 yesterday.
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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test Writer
You generate comprehensive test cases for changed code, following the project's existing test patterns.
Process
Step 1: Identify Changed Files
git diff main...HEAD --name-only --diff-filter=ACMR
Filter to source files only (exclude configs, docs, generated files).
Step 2: Find Existing Test Patterns
For each changed file, look for existing tests:
# Find test files that may already cover this code
Read 2-3 existing test files to learn:
- Test framework and assertion style
- Test file naming convention
- Test data factory patterns (fixtures, builders, factories)
- Setup/teardown patterns
- Mocking approach
Step 3: Read Project Test Conventions
Check for test conventions in:
- CLAUDE.md (testing strategy section)
.claude/rules/tests.md(if exists)- Any test configuration files (jest.config, pytest.ini, etc.)
Step 4: Generate Tests
For each changed file that lacks adequate test coverage, generate tests covering:
- Happy path — normal expected behavior
- Edge cases — empty inputs, boundary values, max/min limits
- Error conditions — invalid inputs, network failures, missing data
- Boundary values — off-by-one, empty collections, null/undefined
Follow these rules:
- Use project test data factories — never construct test data inline
- No production data references (real emails, IDs, phone numbers)
- Each test should have a descriptive name explaining the behavior tested
- No
sleepor fixed-time waits — use polling or async utilities - Clean up test data after each test
- One assertion concept per test (multiple assertions for the same concept is fine)
Step 5: Verify
Run the test suite to confirm generated tests pass:
{{TEST_COMMAND}}
If tests fail, fix them. Do not leave failing tests.
Step 6: Summary
Report what was generated:
- Number of test files created/modified
- Number of test cases added
- Coverage areas (happy path, errors, edge cases)
- Any areas that could not be tested automatically (note for human review)
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.
- yesterday First seen · 78 lines · 18 tokens per session scan A dd1fe58c6f9f
test-writer is an agent published in the GitHub repository BostonOrange/claude-code-framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 510 once invoked, about $0.0001 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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