Skip to main content
Glama
Chaos-Intelligence-Inc

@chaosintelligence/mcp

Official

search_thoughts

Find thoughts semantically matching your query, with optional filters for stream, category, classification, or date range.

Instructions

Search your thoughts using semantic similarity combined with structured filters. Finds thoughts that match the meaning of your query, optionally filtered by stream, category, classification, or date range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to search for semantically
limitNoMaximum results (default: 50, max: 50)
streamNoFilter by stream name (case-insensitive)
categoryNoFilter by category name (e.g., "Technology"). Case-insensitive.
min_scoreNoMinimum similarity score 0-1 (default: 0.5)
stream_idNoFilter by stream ID
category_idNoFilter by category ID
created_afterNoFilter thoughts created after this date (ISO 8601)
classificationNoFilter by classification name (e.g., "task", "idea"). Case-insensitive.
created_beforeNoFilter thoughts created before this date (ISO 8601)
classification_idNoFilter by classification ID
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions semantic similarity but does not disclose whether the operation is read-only, how results are ordered, whether pagination exists, or any potential side effects. This lack of detail about return behavior and constraints leaves significant gaps for an agent.

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 exactly two sentences, front-loaded with the core action ('Search your thoughts'), and every phrase adds value. It avoids redundancy and is appropriately sized for the tool's functionality.

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?

Given the tool has 11 parameters and no output schema, the description should explain what the response contains or how results are structured. It does not mention the return format, ordering by similarity score, or how to interpret the min_score parameter in the results. The description covers the input side but leaves the output side completely unspecified, which is incomplete for an agent.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all 11 parameters. The description summarizes the filter categories (stream, category, classification, date range) which aligns with the schema, but adds no deeper semantic meaning beyond what the schema property descriptions already provide. Thus, it meets the baseline but does not exceed it.

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 clearly states the tool's function: 'Search your thoughts using semantic similarity combined with structured filters.' It uses a specific verb ('Search'), identifies the resource ('thoughts'), and distinguishes itself from siblings like list_thoughts or search_similar by emphasizing semantic similarity plus structured filters.

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?

The description provides clear context for when to use the tool: for semantic search with optional filters by stream, category, classification, or date range. It implies when this is appropriate (semantic queries) but does not explicitly exclude alternatives or mention when not to use it, so it lacks a full exclusionary comparison.

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/Chaos-Intelligence-Inc/chaos-mcp-server'

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