Borrowing it
Nothing to install: this file belongs to sagar-shirwalkar/servicenow-atlas. 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/sagar-shirwalkar/servicenow-atlas/main/.agents/skills/atlas-add-tool/SKILL.mdgit clone --depth 1 https://github.com/sagar-shirwalkar/servicenow-atlasWrote 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/skills/sagar-shirwalkar/servicenow-atlas/atlas-add-tool)<a href="https://agentmods.dev/skills/sagar-shirwalkar/servicenow-atlas/atlas-add-tool"><img src="https://agentmods.dev/badge/skills/sagar-shirwalkar/servicenow-atlas/atlas-add-tool/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/skills/sagar-shirwalkar/servicenow-atlas/atlas-add-tool"><img src="https://agentmods.dev/badge/skills/sagar-shirwalkar/servicenow-atlas/atlas-add-tool.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 | $0.00050 | $0.01026 |
| Opus 5 | $0.00025 | $0.00513 |
| Sonnet 5 | $0.00010 | $0.00205 |
| Haiku 4.5 | $0.00005 | $0.00103 |
Grade A, and why
atlas-add-tool 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 12d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use
- User asks to "add a new tool", "create a tool for X", "expose Y as an MCP tool"
- User is building a new capability that needs to be callable by an LLM
- User wants to understand the existing tool registration pattern
Not for
- General code changes outside tool definitions
- Modifying the embedder or chunker internals
- Changing the MCP server lifecycle (startup, shutdown, transport)
Prerequisites
Read the existing tool implementations in:
atlas/rag_server.py— tools on the RAG server (semantic search, etc.)atlas/fs_server.py— tools on the filesystem server (read, list, search, etc.)
Workflow
1. Locate the right server file
| Tool belongs to | Server file |
|---|---|
| Document search / RAG | atlas/rag_server.py |
| File listing / reading | atlas/fs_server.py |
| Build / maintenance | Consider a new server or atlas/doctor.py |
2. Follow the existing pattern
Each tool has three parts in the server file:
a) Tool docstring + @server.list_tools() handler
@server.list_tools()
async def list_tools() -> list[Tool]:
return [
# existing tools ...
Tool(
name="your_tool_name",
description="What the tool does — be specific",
inputSchema={
"type": "object",
"properties": {
"param_name": {
"type": "string",
"description": "What this parameter is for",
},
},
"required": ["param_name"],
},
),
]
- Tool names:
snake_case, conventionally matching the function name. - Descriptions: written for an LLM reader. Include edge cases, defaults, and example values.
- Parameters: use JSON Schema types (
string,integer,array, etc.). Markrequiredexplicitly.
b) The @server.call_tool() handler branch
@server.call_tool()
async def call_tool(name: str, arguments: dict) -> list[TextContent]:
if name == "your_tool_name":
result = await your_handler(arguments)
return [TextContent(type="text", text=result)]
elif name == "existing_tool":
...
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.
- 12d ago First seen · 132 lines · 50 tokens per session scan A 64216774fdfb
atlas-add-tool is a skill published in the GitHub repository sagar-shirwalkar/servicenow-atlas (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 50 tokens to every session and 1,026 once invoked, about $0.0003 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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