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Intelligent-Context-AI-Inc

ContextECF MCP

Official

context_assemble

Read-only

Assemble a read-only ContextECF context package with preview, selected sources, exclusions, metadata-only evidence references, sufficiency and gap analysis, and receipt metadata.

Instructions

Assemble a read-only governed ContextECF context package with a synthetic assembled-context preview, selected sources, exclusions, metadata-only evidence references, sufficiency, gaps, and receipt metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeIdNoOptional opaque assembly profile id. The public explanation surface is packId plus intentKind.
packIdYes
intentKindYes
timeWindowYes
userRequestYes
responseShapeNo
sourceCapabilitiesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior4/5

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

Beyond the readOnlyHint=true annotation, the description adds meaningful behavioral traits: the result is a 'synthetic assembled-context preview' with 'metadata-only evidence references', indicating the output is not raw evidence or full data. It also lists exclusions/sufficiency/gaps, which helps set expectations about what the package contains. No contradiction with the annotations appears.

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 dense sentence with the main verb and object front-loaded. The long list of package components is somewhat heavy, but each item adds useful information about the assembly output; the structure is still efficient for the scope.

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 no output schema belies the need for the description to explain the return envelope, and it only loosely lists contents. The seven-parameter nested input schema is left largely unexplained, and no guidance is given for how the output shape or synthetic preview behaves. The description provides a high-level inventory but not enough operational detail for an agent to call the tool correctly without further assumptions.

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

Parameters2/5

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

Schema description coverage is only 14%, and the description does not compensate. It references 'selected sources, exclusions' but does not explain how they map to parameters like sourceCapabilities or responseShape, nor does it clarify the required packId, intentKind, userRequest, and timeWindow semantics beyond their names.

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 opens with a specific verb ('Assemble') and a clear resource ('a read-only governed ContextECF context package'), then enumerates the package contents: preview, sources, exclusions, evidence references, sufficiency, gaps, and receipt metadata. This distinguishes it from sibling tools like context_explain or context_evidence, which clearly serve different purposes.

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?

The description gives no explicit guidance about when to use this tool versus the sibling tools (context_explain, context_evidence, context_status, context_feedback). There is no 'use when' or 'use instead' language, so an agent must infer routing entirely from the name and resource wording.

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