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get_context_bundle

Returns a structured JSON payload for a project with project info, entries grouped by type, and artifact references to support AI coding agents.

Instructions

Return structured JSON bundle: project info, entries grouped by type, and artifact refs

Input Schema

NameRequiredDescriptionDefault
projectNoProject name or ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It does useful work by naming the return shape (structured JSON with grouped entries and artifact refs), which is the most important behavioral fact for a read tool with no output schema. It says nothing about read-only safety, size/volume of the bundle, or whether missing projects error or return empty, leaving real gaps.

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?

A single front-loaded sentence with no filler; the payload inventory comes first. It is slightly terse given the agent still needs scoping guidance, but nothing is wasted.

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?

For a low-complexity read tool with one optional parameter and no output schema, the description covers the essentials of what comes back. It stops short of clarifying whether results include historical versions, how large the bundle may be, or what happens with an omitted project, which an agent would need to call it confidently.

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 coverage is 100% and there is only one optional parameter (project), which the schema already documents as 'Project name or ID'. The description adds no format or scoping detail beyond that, 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 (Return) and enumerates the three payload components (project info, entries grouped by type, artifact refs), which is concrete and distinguishes it from entry-level tools like get_entry. However, it does not differentiate itself from the closely-named sibling get_context, leaving genuine ambiguity about which to pick.

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

Usage Guidelines2/5

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

There is no statement of when to use this bundle versus get_context, get_entry, or get_entry_graph. The agent must infer that it is a bulk aggregation call from the description alone, with no explicit context or exclusions.

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