Library of Context

Overview Schema Source Related Servers Discussions Admin

library_prompt_build

Assemble a bounded prompt from recent turns and a reading desk, keeping full history on disk to manage context window size.

Instructions

Build a complete stateless model-input envelope from bounded recent turns plus a replacement reading desk. Full history remains shelved on disk instead of growing the live prompt.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

Name	Required	Description	Default
`max_books`	No
`collection`	No	Optional library collection/namespace; defaults to the configured collection.
`session_id`	No		codex
`record_user`	No
`token_budget`	No
`user_message`	No
`system_prompt`	No
`recent_token_budget`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Aug 21, 2026

TDQS

C2.7/5.0

Behavior3/5

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

The description adds some behavioral context by noting the operation is 'stateless' and that 'full history remains shelved on disk', implying it does not grow the live prompt or modify persistent state. However, it does not disclose permissions, side effects, or failure modes, and the annotations provide no hint (readOnlyHint is false), so the description only partially clarifies the behavior.

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

Conciseness3/5

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

The description is two sentences and mostly front-loaded, but the metaphor 'reading desk' and 'shelved' may obscure meaning without prior library context. It is concise yet could be clearer for the agent, warranting a middle score.

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

Completeness2/5

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

With a complex tool of 8 parameters, 13% schema coverage, no output schema, and no annotations, the description is insufficient. It does not explain the return format, parameter usage, or any side effects. A tool this complex requires richer description to be usable.

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

Parameters1/5

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

Schema description coverage is only 13%, leaving seven of eight parameters undescribed. The tool description does not mention any parameter names or meanings, making it impossible for the agent to understand inputs like 'max_books', 'token_budget', or 'system_prompt'. The description entirely fails to compensate for the schema gap.

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

Purpose4/5

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

The description clearly states the tool 'builds a complete stateless model-input envelope' from bounded recent turns and a replacement reading desk, conveying the core function. However, it does not explicitly differentiate it from similar library tools like library_context_prepare or library_desk_get, leaving its unique role somewhat ambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of scenarios, prerequisites, or exclusions. The description only states what it does, not when it should be invoked, leaving the agent without usage direction.

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

Deploy Server