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tejpalvirk

Developer MCP Server

by tejpalvirk

advancedcontext

Analyze and query the software development knowledge graph to extract insights, track project milestones, explore relationships, and understand decision histories. Use this tool for deep exploration and context-specific information retrieval.

Instructions

A sophisticated tool for advanced querying and analysis of the software development knowledge graph. This tool provides specialized operations to extract meaningful insights and contextual information from the graph structure. It enables deep exploration of projects, components, relationships, decisions, and progress tracking.

When to use this tool:

  • Retrieving the complete development knowledge graph

  • Searching for specific entities using keyword or partial matching

  • Fetching details on a precise set of development entities

  • Exploring all relationships for a specific entity

  • Examining the decision history for a software project

  • Tracking progress toward project milestones

  • Investigating dependencies between components

  • Analyzing the evolution of a software project

  • Understanding the context surrounding development entities

  • Exploring task sequencing and dependencies

  • Identifying entities by status or priority

Key features:

  • Six specialized query operation types

  • Full graph retrieval with entities and relations

  • Keyword-based search across entities and their properties

  • Direct entity lookup by exact name

  • Relationship exploration with filtering options

  • Project decision history with chronological ordering

  • Milestone progress tracking with task status breakdown

  • Status and priority information retrieval

Parameters explained:

  • type: The query operation type to perform, which must be one of:

    • "graph" - Retrieve the entire knowledge graph (all entities and relations)

    • "search" - Find entities by keyword/partial match in name, type, or observations

    • "nodes" - Get specific entities by exact name

    • "related" - Get all entities related to a specific entity

    • "decisions" - Get the decision history for a project

    • "milestone" - Get progress tracking for a specific milestone

  • params: Operation-specific parameters structure:

    • For "graph": No parameters needed

    • For "search": { query: "search text" }

    • For "nodes": { names: ["EntityName1", "EntityName2", ...] }

    • For "related": { entityName: "EntityName", relationTypes: ["type1", "type2", ...] }

    • For "decisions": { projectName: "ProjectName" }

    • For "milestone": { milestoneName: "MilestoneName" }

Operation details:

  • "graph" returns the complete knowledge graph structure

  • "search" performs partial matching on entity names, types, and observations

  • "nodes" retrieves specific entities by exact name matching

  • "related" finds all incoming and outgoing relationships for an entity

  • "decisions" retrieves and chronologically sorts project decisions

  • "milestone" calculates progress percentage and task breakdowns with status information

Notes:

  • Valid status values: "inactive", "active", or "complete"

  • Valid priority values: "low" or "high"

  • Status is represented via the has_status relation type, and priority via has_priority

Return structures:

  • All operations return { success: true/false, ... } with operation-specific data

  • Error responses include detailed error messages

  • "related" returns both incoming and outgoing relationships

  • "milestone" includes progress percentage and task categorization by status

  • Sequencing information appears in directed relationship graphs

You should:

  1. Select the most appropriate query type for your information need

  2. Provide the required parameters for your chosen operation type

  3. Start with broader queries and refine to more specific ones

  4. Use "search" for exploratory investigation when entity names are unknown

  5. Use "related" to explore the neighborhood of a known entity

  6. Use "decisions" to understand the rationale behind project changes

  7. Use "milestone" to evaluate project progress and identify blockers

  8. Analyze task sequencing to understand dependencies and critical paths

  9. Filter entities by status to focus on active, inactive, or completed items

  10. Consider entity priorities when planning work or resolving issues

  11. Combine query results to build comprehensive understanding

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYesParameters for the operation, structure varies by type
typeYesType of get operation: 'graph', 'search', 'nodes', 'related', 'decisions', or 'milestone'
Behavior5/5

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 and does so comprehensively. It details six specialized query operations, explains return structures including error handling, specifies valid status and priority values, and describes how sequencing information appears. It covers behavioral aspects like partial matching, chronological ordering, and progress calculation that aren't inferable from the schema alone.

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

Conciseness3/5

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

The description is well-structured with clear sections (When to use, Key features, Parameters explained, etc.), but it's excessively long with repetitive information. Sentences like 'It enables deep exploration of projects, components, relationships, decisions, and progress tracking' could be more concise, and some details in the 'You should' section overlap with earlier guidance, reducing efficiency.

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?

Given the tool's complexity (6 operation types with varying parameters) and lack of annotations or output schema, the description provides complete context. It covers all operations, parameter structures, return formats, valid values, and usage strategies. The detailed explanations compensate for the missing structured data, making the tool fully understandable for an AI agent.

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

Parameters5/5

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

Despite 100% schema description coverage, the description adds significant value beyond the schema. It explains each 'type' enum value with specific use cases and details the 'params' structure for each operation type, including examples like { query: 'search text' } and { names: ['EntityName1', ...] }. This provides crucial semantic context that the schema's generic descriptions don't cover.

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 purpose as 'advanced querying and analysis of the software development knowledge graph' with specific verbs like 'extract meaningful insights,' 'deep exploration,' and 'tracking progress.' It distinguishes itself from siblings like 'buildcontext' and 'deletecontext' by focusing on query operations rather than creation or deletion.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool with a dedicated 'When to use this tool' section listing 11 specific scenarios (e.g., 'Retrieving the complete development knowledge graph,' 'Exploring all relationships for a specific entity'). It also includes a 'You should' section with 11 actionable recommendations for selecting query types and refining searches, offering clear alternatives and context.

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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