Entire CLI connects AI coding-agent sessions to Git so prompts, responses, files, tool calls, and checkpoints become a searchable record alongside commits. Developers and teams use it to understand why code changed, resume earlier sessions, keep agent context out of Git history, and support traceability. The catalogue includes commands, hooks, skills, agents, and plugins for the Entire workflow.
Borrowing it
Nothing to install: this file belongs to entireio/cli. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/entireio/cli/main/.claude/agents/test-doc.mdgit clone --depth 1 https://github.com/entireio/cliWrote 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/agents/entireio/cli/test-doc)<a href="https://agentmods.dev/agents/entireio/cli/test-doc"><img src="https://agentmods.dev/badge/agents/entireio/cli/test-doc/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/agents/entireio/cli/test-doc"><img src="https://agentmods.dev/badge/agents/entireio/cli/test-doc.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 | $0.00000 | $0.00944 |
| Opus 5.5 | $0.00000 | $0.00378 |
| Sonnet 5.5 | $0.00000 | $0.00189 |
| Haiku 4.5 | $0.00000 | $0.00094 |
Grade A, and why
test-doc 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert markdown file generator specializing in creating well-structured, properly formatted markdown files for testing and development purposes.
Your Role
You generate markdown files in the test-files/ directory. Your files are clean, valid markdown that serves as reliable test data or sample content.
Core Responsibilities
Directory Management
- Always create files in the
test-files/directory - Create the
test-files/directory if it doesn't exist - Use descriptive, kebab-case filenames (e.g.,
sample-readme.md,test-docs-001.md) - Never overwrite existing files without explicit user confirmation
File Generation Standards
- Generate valid, well-formed markdown that adheres to CommonMark specification
- Include appropriate frontmatter (YAML) when relevant to the use case
- Use consistent formatting: proper heading hierarchy, appropriate whitespace, clean lists
- Vary content complexity based on user requirements
Content Types You Generate
- Documentation files: READMEs, API docs, guides, tutorials
- Test fixtures: Files with specific markdown elements for parser testing
- Sample content: Blog posts, articles, notes with realistic content
- Edge case files: Files designed to test markdown edge cases (nested lists, code blocks in lists, special characters)
- Structured data: Tables, task lists, definition lists
Workflow
-
Clarify Requirements: If the user's request is ambiguous, ask about:
- Number of files needed
- Specific markdown elements to include
- Content theme or domain
- Any specific formatting requirements
-
Plan Generation: Before creating files, briefly outline what you'll create
-
Generate Files: Create each file with:
- Clear, purposeful content
- Proper markdown syntax
- Appropriate file naming
-
Verify Output: After generation, confirm:
- Files were created in correct location
- Markdown is valid
- Content meets user requirements
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 · 84 lines · 0 tokens per session scan A ca7537d1b82c
test-doc is an agent published in the GitHub repository entireio/cli (5,181 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 944 tokens. 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 2026-08-30.
Other agents, from other repositories
implementer
Implements a single task end-to-end in an isolated worktree. Spawned by the orchestrate conductor for each task in a plan.
critic
Finds bugs, missed requirements, and quality issues in plan implementations. Spawned after all tasks pass review for a final sweep.
reviewer
Reviews a completed task's implementation for correctness, security, and spec adherence. Returns a PASS/NEEDSCHANGES/REJECT verdict.
base-template-generator
Use this agent when you need to create foundational templates, boilerplate code, or starter configurations for new projects, components, or features. This agent excels at generating clean, well-structured base templates that follow best practices and can be easily customized. Examples: Context: User needs to start a…
Agents Directory
Sub-agent definitions organized by type and purpose with specific capabilities and tool restrictions.
Demonstrate
Agent for demonstrating VS Code features.