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 commands/asachs01/float-mcp/to-reviewgit clone --depth 1 https://github.com/asachs01/float-mcpWrote 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/asachs01/float-mcp/to-review)<a href="https://agentmods.dev/commands/asachs01/float-mcp/to-review"><img src="https://agentmods.dev/badge/commands/asachs01/float-mcp/to-review.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00203 |
| Opus 5 | $0.00000 | $0.00102 |
| Sonnet 5 | $0.00000 | $0.00041 |
| Haiku 4.5 | $0.00000 | $0.00020 |
Grade A, and why
to-review 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.
This is a copy
100% identical to to-review — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Set a task's status to review.
Arguments: $ARGUMENTS (task ID)
Marking Task for Review
This status indicates work is complete but needs verification before final approval.
When to Use Review Status
- Code complete but needs peer review
- Implementation done but needs testing
- Documentation written but needs proofreading
- Design complete but needs stakeholder approval
Execution
task-master set-status --id=$ARGUMENTS --status=review
Review Preparation
When setting to review:
-
Generate Review Checklist
- Link to PR/MR if applicable
- Highlight key changes
- Note areas needing attention
- Include test results
-
Documentation
- Update task with review notes
- Link relevant artifacts
- Specify reviewers if known
-
Smart Actions
- Create review reminders
- Track review duration
- Suggest reviewers based on expertise
- Prepare rollback plan if needed
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 · 44 lines · 0 tokens per session scan A 1d6d95a18ca0
to-review is a command published in the GitHub repository asachs01/float-mcp (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 203 tokens. A static security scan graded it A with 0 findings. It is 100% identical to to-review, differing in 4 lines, and is treated as a copy.
Other commands, from other repositories
tasks
Break down the plan into executable tasks.
plan
Plan how to implement the specified feature.
specify
Start a new feature by creating a specification and feature branch.
review-epo-claims
Analyze patent claims for EPO Art. 84 EPC compliance - clarity, conciseness, support by description.
new
Creates a new item in a module that supports the new capability.
ingest-dev
Ingest a URL, directory, or file into your knowledge base. remember = a specific durable fact, ingest = a URL, learn = a distilled lesson that gets retrieval preference.