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spranab

Project Tracker MCP Server

by spranab

create_context

Preserve understanding across sessions by saving conversation context, chat summaries, or important knowledge.

Instructions

Save conversation context, chat summaries, or important knowledge to preserve understanding across sessions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoTags for categorizing context
titleYesTitle describing the context
contentYesFull context content - conversation summary, decisions made, knowledge learned
metadataNoAdditional metadata like participants, AI model used, etc.
context_typeNoType of context being savedchat_summary
conversation_dateNoDate of the conversation (ISO 8601 format)
related_entity_idNoUUID of related project, epic, or story (optional)
related_entity_typeNoType of related entity (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
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. It says 'save' but does not disclose whether saves require auth, whether duplicate titles are allowed, whether content is indexed/searchable afterward (relevant given search_context), or what happens on conflict. For a mutation tool with zero annotation coverage this is a substantial gap.

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?

One sentence, front-loaded with the verb and resource, with no filler. It is efficient, though it is somewhat generic and spends its words on purpose rather than on operational detail.

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 8 parameters (2 required), nested metadata, two enums, no output schema and no annotations, the description should do more: it never mentions what is returned (e.g., a context ID), how optional fields like related_entity_id are used, or the default context_type behavior. It is too thin for the tool's complexity.

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 explains all 8 parameters including enums and the nested metadata object. The description adds no parameter-level detail beyond what the schema provides, so the baseline 3 applies.

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?

States a specific verb (save) and resource (conversation context, chat summaries, knowledge) plus the outcome (preserve understanding across sessions). It is clear what the tool does, but it does not differentiate itself from close siblings like create_summary or update_context, which the agent would have to distinguish on its own.

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 rationale 'to preserve understanding across sessions' implies the general situation for use, but there is no explicit when-to-use vs when-not, no mention of create_summary/create_issue alternatives, and no prerequisites. Usage guidance is inferable but not stated.

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