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lmdrew96

chaoslimba-mcp-server

by lmdrew96

Add Content Item

cl_add_content

Insert a new content item (reading passage or audio) into the content database during development, specifying type, title, difficulty, duration, topic, and source attribution.

Instructions

Inserts a new content item into the content_items table. Use during dev sessions to seed reading passages, audio content, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesContent type
titleYesContent title
topicYesContent topic
textUrlNoURL to text resource (for text type)
audioUrlNoURL to audio file (for audio type)
transcriptNoFull transcript text
textContentNoText body (for text type)
culturalNotesNoCultural or contextual notes
difficultyLevelYesDifficulty level (1.0–9.5)
durationSecondsYesDuration in seconds
languageFeaturesNoStructured language features (JSONB)
transcriptSourceNoHow the transcript was created
sourceAttributionYesSource/license info
transcriptLanguageNoTranscript language code (default: "ro")

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. While it correctly states that the tool inserts a row into content_items, it does not mention what happens on success/failure, whether an ID is returned, how duplicates are handled, or any side effects beyond the insert. This leaves important behavioral expectations undisclosed.

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 two sentences with no filler: one defines the operation and target, the other gives usage context. It is front-loaded and every sentence earns its place.

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 schema is rich and fully documented, but the description is minimal relative to the tool's complexity (14 parameters, nested objects, no output schema). It correctly frames the tool as a dev-seeding utility, but does not explain expected return behavior, generated fields, or how the inserted item can be referenced afterward.

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 baseline of 3 applies. The description itself adds no parameter-level meaning beyond the schema, but it does not need to because every parameter already has a clear description in the 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 clearly states a specific action ('Inserts a new content item') and the exact resource ('content_items table'), making the tool's purpose unambiguous. It also differentiates from sibling tools like cl_add_reading_question, which operate on a different entity.

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 gives clear usage context: 'Use during dev sessions to seed reading passages, audio content, etc.' This tells an agent when it is appropriate to invoke the tool. However, it does not explicitly mention when not to use it or name alternative tools like cl_add_reading_question.

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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