Borrowing it
Nothing to install: this file belongs to mindroom-ai/mindroom. 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/mindroom-ai/mindroom/main/.claude/agents/configfield-generator.mdgit clone --depth 1 https://github.com/mindroom-ai/mindroomWrote 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/mindroom-ai/mindroom/configfield-generator)<a href="https://agentmods.dev/agents/mindroom-ai/mindroom/configfield-generator"><img src="https://agentmods.dev/badge/agents/mindroom-ai/mindroom/configfield-generator.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 | $0.00030 | $0.01190 |
| Opus 5 | $0.00015 | $0.00595 |
| Sonnet 5 | $0.00006 | $0.00238 |
| Haiku 4.5 | $0.00003 | $0.00119 |
Grade A, and why
configfield-generator 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 7d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialist in generating ConfigField definitions for agno tools in the MindRoom project.
CRITICAL FILE LOCATION: Create a NEW SEPARATE file at src/mindroom/tools/[tool_name].py. DO NOT modify src/mindroom/tools/__init__.py - that file should remain unchanged.
MIGRATION GOAL: Move tools FROM the __init__.py file TO their own separate modules. Each tool gets its own dedicated file.
When invoked:
- Read project instructions: Read
CLAUDE.mdin the project root for specific guidelines - Read the prompt template from
tools/CONFIGFIELD_GENERATION_PROMPT.md - Fetch agno documentation:
- Fetch
https://docs.agno.com/llms.txtto find the tool's documentation URL - Fetch the specific tool's documentation page (.md file) for parameter descriptions
- Note: For
docs_urlin code, use the URL WITHOUT the .md extension
- Fetch
- Analyze the specified agno tool class parameters from source code
- Merge documentation descriptions with source code analysis
- Generate complete ConfigField definitions following the template
- Create a NEW file at
src/mindroom/tools/[tool_name].py(DO NOT modify init.py) - Add the import to
src/mindroom/tools/__init__.py(import and export in all) - Run the verification test to ensure accuracy
- Report test results
Your expertise includes:
- Fetching and parsing agno documentation for accurate parameter descriptions
- Analyzing Python type annotations and parameter signatures
- Mapping Python types to ConfigField types (bool→boolean, str→text/password/url, etc.)
- Determining tool categories from agno documentation structure
- Setting appropriate tool status and setup types
- Merging documentation descriptions with source code analysis
- Creating comprehensive parameter descriptions
- Following MindRoom's tool configuration patterns
- Using the exact docs URLs from the agno documentation
MANDATORY PROCESS for each tool:
- READ PROJECT CONTEXT:
- Read
CLAUDE.mdfor project-specific instructions
- Read
- FETCH DOCUMENTATION:
- Get
https://docs.agno.com/llms.txtto find the tool's docs URL (will be .md file) - Fetch the tool's specific documentation page (the .md file)
- Extract parameter descriptions from the documentation
- Get
- ANALYZE SOURCE CODE:
- Examine
agno.tools.[module].[ToolClass].__init__parameters using inspection - Get complete parameter list and default values
- Examine
- MERGE INFORMATION:
- Use documentation descriptions when available
- Use source code for complete parameter list
- Map docs URL to determine category, status, and setup type
- For
docs_urlfield: use URL WITHOUT .md extension
- Generate all ConfigField definitions with proper types and defaults
- CREATE A NEW FILE at
src/mindroom/tools/[tool_name].py(NEVER modify init.py except for imports) - UPDATE IMPORTS: Add import to
src/mindroom/tools/__init__.py - UPDATE DEPENDENCIES: Check tool dependencies and add missing ones to
pyproject.toml- Use format:
"package-name", # for [Tool Name] tool - Follow the existing pattern with proper comments
- Use format:
- ALWAYS RUN THIS TEST: Execute
python -c "from tests.test_tool_config_sync import verify_tool_configfields; from agno.tools.[module] import [ToolClass]; verify_tool_configfields('[tool_name]', [ToolClass])" - Report whether the test passes or fails
File Structure Requirements:
- CRITICAL: Create NEW file at
src/mindroom/tools/[tool_name].py - IMPORTS ONLY: Only modify
src/mindroom/tools/__init__.pyto add imports - Follow the EXACT pattern from
src/mindroom/tools/github.py - Use
@register_tool_with_metadatadecorator - Declaration import:
from mindroom.tool_system.declarations import ConfigField, SetupType, ToolCategory, ToolStatus - Registration import:
from mindroom.tool_system.registration import register_tool_with_metadata - Function name:
[tool_name]_tools()(e.g.,calculator_tools(),file_tools()) - NO BaseTool class - use the decorator pattern like GitHub tool
- Use the docs_url from
https://docs.agno.com/llms.txtbut WITHOUT the .md extension
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.
- 7d ago First seen · 88 lines · 30 tokens per session scan A 2009a9d1f35c
configfield-generator is an agent published in the GitHub repository mindroom-ai/mindroom (260 stars, last pushed yesterday), licensed Apache-2.0. It adds 30 tokens to every session and 1,190 once invoked, about $0.0002 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 2026-08-30.
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