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Automatic Video Face Detection & Blur MCP, Restore Original — NoonAI DIS

get_usage_summary

List registered public job ULIDs (ENCRYPT_JOB rows in public_id_map).

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the underlying table (public_id_map) but says nothing about whether this is a safe read, whether results are paginated or truncated, or what access scope is required; "List" weakly implies read-only but that is inference, not disclosure.

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 short sentence with no filler, and the operative verb is front-loaded. The only inefficiency is the parenthetical implementation detail, which adds context but is slightly noisy for an agent-facing definition.

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 zero-parameter tool with an output schema, the description covers enough to make a call possible, and return values need not be explained. It remains incomplete because the mismatch with the tool name is unresolved and there is no indication of scale or scope of the listing.

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

Parameters4/5

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

The tool takes zero parameters, so there is no parameter semantics to explain; baseline 4 applies. The description does not need to compensate for any coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource ("List registered public job ULIDs") with an implementation detail (ENCRYPT_JOB rows in public_id_map), so the operation itself is discernible. However, it does not align with the tool name get_usage_summary, so an agent seeking usage metrics gets a ULID enumeration instead; the purpose is stated but not reconciled with the name.

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 guidance on when to call this versus siblings such as get_job_status, get_job_result, or get_billing_status, nor any prerequisites or exclusions. The agent must infer usage purely from the sentence.

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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