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Get influencer snack pack status

get_influencer_snack
Read-only

Poll a snack pack started by generate_influencer_snack. Returns status/progress; when completed, the rendered assets are attached as resource links and the result carries the dashboard viewUrl. Then list_influencer_snacks will include the finished pack.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesJob id returned by generate_influencer_snack
influencerIdYesInfluencer id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, non-destructive, closed-world). The description adds real behavioral context beyond annotations: it's a polling tool, it returns status/progress, completed state attaches rendered assets as resource links, and the result carries a dashboard viewUrl. It doesn't state any polling interval or terminal error states, but the completion behavior is well disclosed.

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 tightly packed sentences, each earning its place: what it does, what completion yields, and the follow-up sibling. Front-loaded with the action and zero filler.

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 2-param polling tool with a full schema and annotations covering safety, the description supplies the lifecycle, completion payload description, and downstream linkage. No output schema exists, and the description conveys the key return concepts (status/progress, asset links, viewUrl), which is sufficient; a bit more on failure/in-progress polling guidance would make it a 5.

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 both parameters are documented in the schema (jobId explicitly notes it comes from generate_influencer_snack). The description restates the jobId lineage but adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

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?

States a specific verb+resource (poll a snack pack job) and explicitly ties the lifecycle to the sibling that creates it (generate_influencer_snack) and the sibling that lists the finished result (list_influencer_snacks). An agent can distinguish this from get_snack and get_job without opening schemas.

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

Usage Guidelines5/5

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

Explicitly names the prerequisite (started by generate_influencer_snack) and the downstream action (list_influencer_snacks will then include the finished pack). The lifecycle sequence makes when-to-use vs. siblings unambiguous.

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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