run_algorithm

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

With no annotations provided, the description carries full burden and adds significant behavioral context: it discloses async processing ('Returns a job_id for async processing'), cost implications ('Requires credits'), and input alternatives (media_url vs media vs text). It doesn't mention rate limits or error behaviors, but covers core operational traits.

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

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

Three sentences with zero waste: first states purpose and inputs, second explains async nature and polling, third notes credit requirement. Each sentence earns its place by providing essential information not obvious from other fields.

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

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

For a complex tool with 9 parameters, no annotations, and no output schema, the description does well: it covers purpose, usage, async behavior, and cost. It could mention error cases or output format, but given the schema's 100% coverage and explicit sibling references, it's largely complete.

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

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 all 9 parameters thoroughly. The description adds minimal value beyond schema: it mentions algorithm IDs come from 'list_algorithms' and text is for 'text algorithms like spectra, textmark', but doesn't provide additional syntax or format details. Baseline 3 is appropriate when schema does heavy lifting.

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

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

The description clearly states the specific action ('Run one or more named algorithms on media') and identifies the resource ('media'). It distinguishes from siblings by specifying algorithm IDs come from 'list_algorithms' and mentions text processing as an alternative, differentiating from tools like 'detect_ai' or 'protect_media'.

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

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

Explicit guidance is provided: when to use ('on media'), prerequisites ('algorithm IDs from list_algorithms'), alternatives ('text param for text algorithms'), and next steps ('use check_job to poll for results'). It clearly distinguishes from sibling tools by specifying the processing context.

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