Skip to main content
Glama

knitbrain_optimize

Compresses JSON, code, or prose into a token-efficient skeleton with local storage for lossless recovery via the returned hash.

Instructions

Compress a payload (JSON / code / prose) into a token-cheap skeleton. The exact original is stored locally and recoverable via knitbrain_retrieve using the returned ⟨ccr:hash⟩. Returns the original unchanged if compression wouldn't help.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe payload to optimize.
Behavior4/5

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

Discloses that compression is lossy ('token-cheap skeleton'), that original is stored locally, and that it returns unchanged if ineffective. Full burden carried as no annotations provided.

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?

Three concise sentences with front-loaded action. Every sentence adds value with no redundancy.

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

Completeness5/5

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

For a simple tool with one param and no output schema, description covers purpose, usage, behavior, and edge cases (no compression). Fully complete.

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

Parameters4/5

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

Schema coverage is 100% with good param description. Adds context on input types and compression behavior, boosting understanding beyond schema alone.

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?

Clearly states the verb 'compress' and the resource 'payload', specifying types (JSON/code/prose). Distinguishes from sibling by mentioning recoverability via knitbrain_retrieve.

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

Usage Guidelines4/5

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

Describes recovery option and no-op case, giving context for when to use and when not. However, lacks explicit exclusion criteria or comparison to other tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/PDgit12/knitbrain'

If you have feedback or need assistance with the MCP directory API, please join our Discord server