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MarkAC007

mcp-server-scf

by MarkAC007

scf_bulk_assess_evidence

Queue AI assessments for multiple evidence files by evidence ID, file IDs, or unassessed status; returns count queued.

Instructions

Queue AI assessments for multiple evidence files (write — editor+ role, async, max 50). Provide evidence_id, file_ids, and/or assess_unassessed. Returns count queued.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
org_idYesOrganization UUID — obtain from scf_list_organizations
file_idsNoSpecific evidence file UUIDs to assess
evidence_idNoEvidence ID — assesses every file under this evidence item
assess_unassessedNoAlso assess every file that has no existing assessment (default false)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.7.0

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only indicate readOnlyHint=false and destructiveHint=false; the description adds meaningful behavior: the operation is a write, requires editor+ role, is asynchronous, caps at 50 files, and returns a queued count. This goes well beyond the structured annotations.

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?

Three short sentences pack the essential facts: purpose, role, async behavior, batch limit, input options, and return value. Every clause earns its place and the most important constraints are front-loaded.

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?

For a four-parameter tool with no output schema, the description covers the operation, permissions, async behavior, limits, selector inputs, and return value. It is slightly incomplete in not stating explicitly that at least one of evidence_id/file_ids/assess_unassessed is practically needed to do useful work.

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 documents each parameter. The description's 'Provide evidence_id, file_ids, and/or assess_unassessed' adds minimal grouping guidance but does not meaningfully clarify syntax or semantics beyond the schema.

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 names a specific verb ('Queue'), a specific resource ('AI assessments for multiple evidence files'), and key constraints (write, editor+ role, async, max 50). The bulk scope clearly distinguishes it from single-file assessment tools.

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 tells the agent what to provide ('evidence_id, file_ids, and/or assess_unassessed') and conveys the async nature and batch limit. It does not explicitly contrast with close siblings like scf_trigger_evidence_assessment, so it stops short of full when-to-use/when-not-to-use guidance.

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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