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MarkAC007

mcp-server-scf

by MarkAC007

scf_get_cdm_document_map

Retrieve a per-domain coverage map of ingested documents to identify silent SCF domains and documentation gaps. Provide an organization UUID to get the map.

Instructions

Get the CDM document map (read — viewer role): per-domain coverage showing which ingested documents speak to which SCF domains, and where the corpus is silent. Finds documentation gaps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
org_idYesOrganization UUID — obtain from scf_list_organizations
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that it is a read operation and viewer role, which implies safety and permission level. It also explains that it returns per-domain coverage and identifies silent areas. However, it does not describe the output format in detail, potential pagination, or any side effects. For a simple read with a single param, this is adequate but not rich.

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

Conciseness5/5

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

The description is a single, concise sentence that front-loads the primary purpose and includes a parenthetical for role. It avoids redundancy and every clause adds meaning. It is well-structured and efficient.

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

Completeness4/5

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

Given the low complexity (one parameter, no output schema), the description is fairly complete. It explains what the tool returns (per-domain coverage, silent areas) and implies the output is a map. It could explicitly state the return type (e.g., a JSON object) but the textual description is sufficient for an agent to understand the result. It lacks error conditions, but for a read-only tool of this simplicity, that is acceptable.

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?

The schema has 100% coverage for the only parameter org_id, with a description explaining where to obtain it (scf_list_organizations). The tool description does not add additional parameter semantics beyond reinforcing that the map is organization-specific. Since the schema already explains the parameter adequately, a baseline of 3 is appropriate.

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 states a specific verb and resource ('Get the CDM document map') and elaborates on what it shows: per-domain coverage of ingested documents relative to SCF domains and silent areas. It distinguishes itself from sibling tools like scf_list_cdm_documents (which lists documents) and scf_query_cdm_corpus (which queries the corpus) by focusing on coverage mapping and gap identification.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool: to assess per-domain documentation coverage and find gaps. It mentions 'read — viewer role' implying it's a safe read. However, it does not explicitly name alternative tools or state when not to use it, such as when needing raw document lists or specific document details. It could be improved by referencing alternatives, but the purpose is clear enough to infer usage.

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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