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/BostonOrange/claude-code-frameworkWrote 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/commands/bostonorange/claude-code-framework/quick-test)<a href="https://agentmods.dev/commands/bostonorange/claude-code-framework/quick-test"><img src="https://agentmods.dev/badge/commands/bostonorange/claude-code-framework/quick-test/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/commands/bostonorange/claude-code-framework/quick-test"><img src="https://agentmods.dev/badge/commands/bostonorange/claude-code-framework/quick-test.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 | $0.00012 | $0.00112 |
| Opus 5 | $0.00006 | $0.00056 |
| Sonnet 5 | $0.00002 | $0.00022 |
| Haiku 4.5 | $0.00001 | $0.00011 |
Grade A, and why
quick-test 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 5d 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.
What it actually says
Run tests scoped to files changed since the base branch.
Steps
- Get changed files:
git diff {{BASE_BRANCH}}...HEAD --name-only --diff-filter=ACMR
- Run tests on changed files:
{{TEST_COMMAND}}
- Report pass/fail summary. Do not attempt to fix failures — just report what passed and what failed with error details.
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.
- 5d ago First seen · 22 lines · 12 tokens per session scan A c8b81d203053
quick-test is a command published in the GitHub repository BostonOrange/claude-code-framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 112 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 2026-09-03.
Other commands, from other repositories
implement-feature
Implement an approved feature plan with fresh-context slices, TDD, evidence, and PR-ready output.
red-team
Stress-test a plan, strategy, PRD, or launch with a room of hostile expert personas before you commit.
CLAUDE
When debugging TUI commands like wt switch (interactive picker), use the tmux-cli skill (preferred) or MCP's node-terminal tools to test interactively.
pr-ready
Run the project's pre-commit review loop to determine whether the current branch is ready to push — lint, tests, parallel pr-review-toolkit agents plus an over-engineering audit, fix-and-re-run until convergence.
check-fix
Execute quality gates, fix any issues found, and create a single high-quality Conventional Commit summarizing all changes made.
verify
Run verification commands and confirm output before making success claims. Use before committing, creating PRs, or claiming work is complete. Evidence before assertions, ALWAYS.