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timeline-mcp

by bmit20

summarize_timeline_context

Generate a short timeline-aware summary from structured timeline state for insertion into an LLM system prompt or tool context.

Instructions

Generate a short timeline-aware summary for insertion into an LLM system prompt or tool context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeline_stateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says it generates a summary, with no mention of whether the operation is read-only, whether it modifies any state, what the output format is, or any constraints. For a tool with zero annotation coverage, this is insufficiently transparent.

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

Conciseness4/5

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

The description is a single well-formed sentence that front-loads the core verb and object. It uses no unnecessary words and is appropriately sized for a straightforward tool. It could be more informative, but for what it contains, it is concise and structured.

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

Completeness1/5

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

With one nested object parameter, no output schema, and no annotations, the description must compensate by explaining what timeline_state is and what the summary looks like. It does neither, leaving the agent to guess about input structure and return format. This is a significant gap for a tool that is meant to be invoked correctly.

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?

The only parameter timeline_state has 0% schema description coverage, and the description does not mention it at all. 'Timeline-aware' hints at the input's role, but does not explain what timeline_state should contain or how it relates to the summary. The description adds no semantic value for the parameter beyond the schema's bare object type.

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 states a specific action ('Generate') and resource ('short timeline-aware summary'), and identifies the use case ('insertion into an LLM system prompt or tool context'). This is clear enough to distinguish it from sibling tools like extract_timeline_events or days_since_event, though it could be more explicit that it summarizes a timeline_state object.

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

Usage Guidelines3/5

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

The description implies usage by stating the output is intended for system prompts or tool context, giving context for when to use it. However, it provides no explicit comparison to sibling tools, no conditions that select it over alternatives, and no mention of prerequisites or exclusions.

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