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keystone-mcp

keystone-mcp

by tacoda
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

keystone_new_prompt

Scaffold a markdown prompt file that specifies a reasoning task for an agent to read and perform. Used by inferential sensors to drive reasoning.

Instructions

Scaffold a prompt markdown under .keystone/harness/prompts/<name>.md.

Used by inferential sensors — the agent reads the prompt and performs the reasoning task it describes. Most projects scaffold inferential sensors via keystone_new_sensor(mode="inferential") which stamps the matching prompt automatically.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "keystone_new_prompt"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyNo
nameYes
forceNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the scaffold effect (creating a markdown file) but does not mention side effects like overwriting behavior, what 'force' does, or whether the operation is safe or destructive. The description is too sparse on behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the main purpose. Every sentence adds context, and it avoids unnecessary repetition of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core purpose and relation to inferential sensors, and an output schema exists to explain return values. However, it omits key behaviors (body/force semantics) and does not fully contextualize when to use this tool versus other new_* siblings beyond new_sensor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It only hints at the 'name' parameter via the file path template. The 'body' and 'force' parameters are completely unexplained, leaving significant gaps in understanding the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Scaffold' with a clear resource: a prompt markdown file under a defined path. It distinguishes itself from sibling tools by explaining the inferential sensor connection and explicitly mentions keystone_new_sensor as the alternative that stamps the prompt automatically.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: this tool is for inferential sensors. It also provides an explicit alternative: most projects should use keystone_new_sensor(mode='inferential') instead, which implies when to prefer the sibling over this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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